Bayesian Health jobs

Physician Consultant (Part Time) Remote, United States In Brief - We're an early-stage startup that's building a health AI platform to help clinicians make better use of real-time data to reduce preventable complications and save patient lives. - We're looking for board certified physicians with at least 5 years of clinical experience who have also participated in clinical studies for regulatory submission. Who We Are We're using state-of-the-art tech to build AI co-pilots for doctors and nurses to literally help them save lives! Read more here about the recent publication on the cover of Nature Medicine of our large, two-year study of the effectiveness of our platform. We're not afraid of hard problems and are highly results-oriented. We also like to have fun while we're working on hard things. Our culture is highly collaborative, inclusive, supportive, and we have a strict “no jerks” policy. We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognition includes: AI Top 50, World Economic Forum Tech Pioneer, UCSF Digital Health Top 3 emerging startups in digital health. Who You Are - MD, MBBS, or DO - Board certified in Medical or Surgical Critical Care (CC), Infectious Diseases (ID), Emergency Medicine (EM), Internal Medicine (IM), General Surgery (GS) or related fields - At least 5 years of clinical experience - Prior experience with clinical informatics or clinical decision support tools - Prior clinical trials experience

Software Engineer, Analytics Remote - US Only, United States Software Engineer, Analytics In Brief - We're an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - You will lead the development of our clinical AI/ML product analytics infrastructure, frameworks, and tools to enable our client success, product, clinical, and technology teams to uplevel our decision making through better insights. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What you'll do As a Senior Software Engineer, Analytics, you will work closely with client success, product managers, clinicians, data scientists, and other software engineers to build infrastructure, frameworks, and tools to improve client analytics, facilitate clinical case reviews, and support product investigation. This role is crucial to provide

Infrastructure Engineer Remote - US Only, United States In Brief - We're a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - You will build and maintain the infrastructure for the Bayesian platform and develop CI/CD to enable other team members such as software engineers, data scientists, etc. to accelerate their development will drive expansion of our clinical AI/ML module offerings, health system enterprise-wide implementations, and revenue growth. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What you'll do As an Infrastructure Engineer, you will build and maintain the networking and infrastructure for the Bayesian platform and develop CI/CD pipelines to enable other team members such as software engineers, data scientists, etc. to accelerate their

Enterprise Growth Lead Remote, United States Enterprise Growth Lead In Brief - We're a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - We are looking for an experienced, motivated Enterprise Growth Lead to lead revenue growth in a territory. In this role, you will develop and execute a sales and account growth strategy to drive adoption of our solutions across health systems. You'll be at the forefront of our mission, working closely with hospital executives and clinical leaders to bring our groundbreaking technology to life. Who We Are We're using state-of-the-art tech to build AI co-pilots for doctors and nurses to literally help them save lives! Read more about our recent publication in Nature Medicine that associates our products with lives saved. We're a diverse and experienced team of AI/ML experts, software engineers, product designers, behavior change specialists, and clinicians. We're not afraid of hard problems and are highly results-oriented. We also like to have fun while we're working on hard things. Our culture is highly collaborative, inclusive, supportive, and we have a strict “no jerks” policy. We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Who You Are - Proven Commercial Leadership:

Client Success Account Executive, Clinical Remote - US Only, United States Client Success Account Executive, Clinical In Brief - We're a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - Lead clinical health system accounts through strategic implementation and lifecycle management, utilizing data to drive adoption, optimize outcomes, and unlock expansion opportunities across clinical modules. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What You'll Do As a Client Success Account Executive, Clinical, you become the strategic face of Bayesian for health system clients, guiding them from implementation through their entire lifecycle. You'll cultivate executive relationships, design stakeholder engagement strategies, and lead cross-functional teams to drive product adoption and clinical outcomes. Your clinical expertise allows you to

Software Engineer, Full Stack Remote - US Only, United States Software Engineer, Full Stack In Brief - We're a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - You will work closely with product managers, clinicians, data scientists, and other software engineers to build world-class clinical AI/ML products with direct positive impacts to frontline users within leading enterprise health systems. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What you'll do As a Software Engineer, you will be instrumental in the development and deployment of our clinical AI/ML products within leading enterprise health systems, involving close collaboration with product managers, clinicians, data scientists, and other engineers. Your contributions will be critical for expanding our product

Director of AI/ML Remote - US Only, United States Director of AI/ML In Brief - We're an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - Lead Bayesian Health's AI/ML organization with a hands-on, scrappy approach: setting technical vision, rolling up your sleeves on critical modeling work, and building a world-class team that ships breakthrough ML products saving lives in hospitals nationwide. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What you'll do As Director of AI/ML, you'll set the technical vision and strategy for Bayesian Health's machine learning organization while building and leading a high-performing team of data scientists and ML engineers. You'll partner deeply with Engineering to architect scalable data warehousing and ML infrastructure that enables

Staff Machine Learning Engineer Remote, United States Staff Machine Learning Engineer In Brief - We're an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - Part Data Scientist (building models), part Applied Scientist (productionizing models), and part MLE (deploying, maintaining), also known as “Full Stack Data Scientist” - someone who wants to own the end-to-end effectiveness of their real-time models in a live, clinical AI product. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What You'll Do As a Staff Machine Learning Engineer, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you

Forward Deployed Software Engineer, Full Stack Remote - US Only, United States Forward Deployed Software Engineer, Full Stack In Brief - We're an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - You will lead and optimize enterprise-level client technical implementations, and help us build our growing Forward Deployed Engineering team. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What you'll do Lead the integration of our clinical AI platform and application with our health system clients' electronic health records (EHR) involving cross-functional collaboration with Client Success, Clinical, Product, and Data Science. You'll play an important role in building automation and tooling to reduce integration resources and timeline that's crucial as we expand our client base.

Senior/Staff Machine Learning Data Scientist Remote - US Only, United States Senior/Staff Machine Learning Data Scientist In Brief - We're an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. - TLDR : Independent end-to-end model development with ability to work cross-functionally with Clinical, Engineering, and Product to clarify and prioritize specifications and features for our life-saving AI models. Who We Are Bayesian Health's mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We're a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We're funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association's venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What you'll do As a Senior/Staff Machine Learning Data Scientist, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you aren't afraid to get your hands dirty

Senior Staff Data Scientist - Bayesian Experimentation & Causal Inference New York, New York, United States; San Francisco, California, United States; Seattle, Washington, United States 1 in 4 people in the US have a treatable mental health condition, but most providers don't accept insurance, making therapy too expensive for most people. Headway's mission is to fix this by building a new mental healthcare system everyone can access. We started by solving the biggest barrier to care: insurance. The admin work - credentialing, claims, payment reconciliation - is a nightmare. We've automated that. But we're going further. Over 75,000 providers across all 50 states run their practice on our software, serving over 1 million patients. We are building the best tools for therapists to run their entire practice, reimagining the experience of finding a therapist, and investing in the platform foundations to enable this at scale. We aren't just a billing layer; we are becoming the platform where care actually happens. We're a Series D company with $325M+ in funding (a16z, Accel, Spark Capital, etc.), looking for exceptional people to help us achieve this mission. We want your time here to be the most meaningful experience of your career. Join us, and help change mental healthcare for the better. Join us to build the truth engine behind better mental health outcomes. As a Senior Staff Data Scientist, Bayesian Experimentation and Causal Inference , you will be the company-wide owner of how Headway learns from data, especially when the stakes are high

Researcher, Health AI San Francisco, California, United States About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models towards their deployment in the real world. OpenAI's charter calls on us to ensure the benefits of AI are distributed widely. Our Health AI team is focused on enabling universal access to high-quality medical information. We work at the intersection of AI safety research and healthcare applications, aiming to create trustworthy AI models that can assist medical professionals and improve patient outcomes. About the Role We're seeking strong researchers who are passionate about advancing AI safety and improving global health outcomes. As a Research Scientist, you will contribute to the development of safe and effective AI models for healthcare applications. You will implement practical and general methods to improve the behavior, knowledge, and reasoning of our models in these settings. This will require research into safety and alignment techniques that we aim to generalize towards safe and beneficial AGI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design and apply practical and scalable methods to improve safety and reliability of our models, including RLHF, automated red teaming, scalable oversight, etc. - Evaluate methods using health-related data, ensuring models provide accurate, reliable, and trustworthy information. - Build reusable libraries for applying general alignment techniques to our models.

Research Scientist San Francisco | OnSite RESEARCH SCIENTIST ABOUT LATENT HEALTH Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For everyone else, care is fragmented and impersonal. Medical history is scattered across systems that don't communicate. Physicians have minutes to understand decades of context. And when something goes wrong, patients are left with tools that understand medicine broadly-but not the individual. We believe this can be fundamentally rebuilt. At Latent Health, we are building systems that understand both: - the population (clinical knowledge at scale) - and the individual (longitudinal patient history) Our models are designed to answer complex clinical questions with patient-specific context and verifiable reasoning. Our dataset represents one of the most clinically diverse populations in the United States, including patients with chronic illness and complex disease. Each patient record contains extraordinary depth. ML AT LATENT HEALTH The Machine Learning team is responsible for building systems that run in real clinical workflows. We work on: - Verifiable reinforcement learning at scale - Mid-training and post-training of foundation models - Novel objectives derived from longitudinal patient data We are a small group of researchers and engineers focused on pushing the frontier while shipping real systems into production. We are a small team and expect engineers to take ownership of critical systems, not components. THE ROLE As a Machine Learning Engineer, Research, you will own the design and development of novel modeling approaches that advance state-of-the-art

Machine Learning Research Scientist - Health AIML Seattle, United States of America The Health AIML team is at the forefront of machine learning and health science at Apple. We are a close-knit team of research scientists, software engineers and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a Machine Learning Research Scientist with strong dedication to solving real-world problems in health and fitness that enrich our customers' lives. We're developing next-generation multimodal models to create intelligent health and fitness experiences. This role requires someone with strong expertise in large multimodal models to work at the intersection of AI and health to build foundational models that scale to billions of users worldwide. Your work will shape the future of health and fitness technologies at Apple. We are looking for a research lead to guide multimodality research. You will lead the development of foundational technology that enables models to understand health and fitness data. Lead research into health and fitness representation models and multimodal models. Design, prototype and scale up new architectures to improve model intelligence. Execute and analyze experiments autonomously and collaboratively. Study, debug, and optimize model performance and computational performance. Contribute to training and inference infrastructure. Guide technical and architectural decision. Minimum Qualifications: PhD in Computer Science/Engineering, Machine Learning, Statistics, Mathematics or related field. Industry work experience. Experience landing contributions to major LLM training runs. Proven track record of publishing SOTA. Strong skills with deep learning frameworks such as PyTorch, JAX,

Staff Machine Learning Engineer (Health) Boston, MA WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives. The Health team is responsible for developing novel algorithms and features that expand our health sensing capabilities. Our work spans several key areas, including women's health, software as a medical device, wellness monitoring, longevity research, and emerging health insights. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members. As a Staff Machine Learning Engineer on our Clinical Health team, you will design, build, and productionize ML systems that deliver meaningful, personalized health insights to millions of members. You will work at the intersection of software as a medical device (SaMD), machine learning, backend engineering, and cloud infrastructure-deploying robust, scalable, and reliable ML solutions built on physiological and behavioral data streams. A central part of this role is collaborating with crossfunctional teams that own regulatory, quality, and clinical strategy, to ensure our algorithms are developed with the rigor required for regulated software. This role emphasizes strong coding skills, system design, and the ability to deliver production-ready ML services within a quality-managed framework. WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a

Machine Learning Engineer - Health AIML Boulder, United States of America The Health AI team is at the forefront of machine learning and health science at Apple. We are a close-knit team of highly accomplished, deeply technical research scientists, software engineers, and machine learning engineers passionate about delivering innovative technologies that impact millions of users. We are looking for a senior engineer excited about solving real-world problems in the health domain that make a difference in our customers' lives. In this role, you will use your skills and experience in software engineering, machine learning, deep learning, and generative AI to design, implement, tune, and evaluate machine learning models and systems. You will solve ambitious problems involving unique data and high-impact products, including state-of-the-art generative AI technologies. The successful candidate should possess excellent interpersonal skills and the ability to work cross-functionally to rapidly apply engineering best practices and novel research techniques at the intersection of Health, ML, and consumer products. Minimum Qualifications: 10+ years of overall software development experience. Experience leading a team and/or a proven track record of cross-functional collaboration to deliver customer-facing features with machine learning capabilities in production. BS/MS/Ph.D. in Computer Science, Computer Engineering, Machine Learning, or related fields (or equivalent qualification). Preferred Qualifications: Ph.D. in Computer Science, Machine Learning, or a related field. Strong background in generative models, natural language processing (NLP), and large language models (LLMs). 5+ years of hands-on experience in state-of-the-art machine learning and deep learning applied to large-scale datasets and/or production applications. Proficiency

Machine Learning Engineer / Scientist Bay Area Until is a moonshot company building a “pause button” for biology. Our near-term focus is organ-scale reversible cryopreservation: preserving donated organs at subzero temperatures without ice formation, then rewarming them uniformly for transplant. By solving this grand challenge, we're laying the foundation for whole-body reversible cryopreservation, giving patients a bridge to future cures. To achieve our goal, we are assembling an interdisciplinary team to develop perfusion systems, cryoprotectant formulations, and vitrification and rewarming hardware. We are also building out our medical hibernation team to tackle the challenges of whole-body cryopreservation, beginning with rodent models. We envision a future where no transplantable organ is lost to logistics, and no terminal diagnosis is final because patients can safely wait for future medicine to arrive. About the Role As a Machine Learning Engineer / Scientist at Until, you will be an early member of the computational team defining how experimental data becomes insight and drives the next round of scientific discovery. You'll build high-leverage ML systems that help develop new cryoprotectant formulations, engineer biologically-inspired antifreeze proteins, and understand the physics of vitrification and rewarming. You will own projects end-to-end including shaping data collection and designing data pipelines, training and evaluating models, and deploying tooling that scientists use daily. Until is a moonshot company building a “pause button” for biology. Our near-term focus is organ-scale reversible cryopreservation: preserving donated organs at subzero temperatures without ice formation, then rewarming them uniformly for transplant. By solving this grand challenge,

Machine Learning Engineer San Francisco | OnSite MACHINE LEARNING ENGINEER ABOUT LATENT HEALTH Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For everyone else, care is fragmented and impersonal. Medical history is scattered across systems that don't communicate. Physicians have minutes to understand decades of context. And when something goes wrong, patients are left with tools that understand medicine broadly-but not the individual. We believe this can be fundamentally rebuilt. At Latent Health, we are building systems that understand both: - the population (clinical knowledge at scale) - and the individual (longitudinal patient history) Our models are designed to answer complex clinical questions with patient-specific context and verifiable reasoning. Our dataset represents one of the most clinically diverse populations in the United States, including patients with chronic illness and complex disease. Each patient record contains extraordinary depth. ML AT LATENT HEALTH The Machine Learning team is responsible for building systems that run in real clinical workflows. We work on: - Verifiable reinforcement learning at scale - Mid-training and post-training of foundation models - Novel objectives derived from longitudinal patient data We are a small group of researchers and engineers focused on pushing the frontier while shipping real systems into production. We are a small team and expect engineers to take ownership of critical systems, not components. THE ROLE As a Machine Learning Engineer, you will own the design, development, and operation of production-grade ML systems that

Senior Machine Learning Engineer United States - Remote This team spans many time zones. Most team meetings are between 8 and 11 am EST. Attendance is required for this role. Our Mission Function Health is the AI operating system for health, designed to empower people to live 100 healthy years. We are redefining how individuals understand, measure, and improve their health by moving beyond reactive care and enabling proactive, data-driven insight into human biology. Function has been recognized as one of Fast Company's Most Innovative Companies of 2024 , and is venture-backed by Andreessen Horowitz (a16z) . Hundreds of thousands of members have joined Function to take control of their health. Through advanced diagnostics, deep biomarker testing, longitudinal data, and AI-enabled insights, Function equips members with actionable intelligence to take control of both the quality and length of their lives. Function recently announced a $298M Series B and is entering its next chapter of growth. As we scale, the quality and durability of our People systems, data, and insights will directly shape our ability to attract, retain, and support exceptional talent. Function's newly launched Medical Intelligence Lab (MIL) is charged with building the operating system that converts individual and population health data into health guidance. In essence, MIL is building a GPS for health - a system which understands where you have been, has mapped the health landscape around you, and steers you where you need to go to avoid disease and arrive at healthy longevity. MIL brings together engineers,

Staff Data Scientist, (Global Security) TORONTO, Ontario, Canada Embrace the role of a Staff Data Scientist and lead advanced analytics projects using PySpark, Python, and Bayesian statistics. Mentor junior scientists, build robust machine learning models, and drive innovation in data science for global security. Shape impactful solutions in a collaborative, high-performing environment. Grow your career with us in Toronto!

Senior Machine Learning Engineer (Data Science Algorithms) Boston, MA WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives. Our data science algorithms teams are responsible for developing novel algorithms and features that expand our health and fitness capabilities with medical-grade metrics. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members. Currently, we have two Senior MLE roles open across two teams: DS Health team: novel algorithms within the domains of women's health, multimodal longitudinal health insights, and SaMD DS Core Algos team: performance-related insights for sleep, recovery, or exercise As a Senior Machine Learning Engineer on our Core Algos or Health team, you will design, build, and productionize ML systems that deliver meaningful, personalized health metrics to millions of members. You will work at the intersection of data science, backend engineer, and cloud infrastructure - deploying robust, scalable, and reliable ML solutions build on physiological and behavioral data streams. This role emphasizes strong coding skills, system design, and ability to deliver production-ready ML systems. WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives.

Staff Data Scientist (Global Security) TORONTO, Ontario, Canada Embrace the role of a Staff Data Scientist and lead the analysis of global security datasets using Python, Spark, and Bayesian statistics. Oversee multiple projects, mentor junior scientists, and drive impactful solutions in a collaborative environment. Shape the future of data-driven security with us!

Location Estimation Engineer, Sensing & Connectivity Cupertino, United States of America Develop and improve multi-sensor navigation technology as a location estimation engineer. Craft the next generation of location-aware mobile experiences by working on state-of-the-art technologies to seamlessly integrate people's digital and physical lives. Are you passionate about building technology that will make a difference? Do you flourish with good creative challenges? Do you love attention to detail? If so, we might just be the team for you. Here at Apple, we build devices and services that enrich our customers' lives. In the location technologies group, we help people connect: with each other, and with our planet. We reach more than a billion people. We help them find their way, and we help them find each other. We help them stay healthy, and sometimes we even save their lives. What we do and how we do it makes a difference. Join our team, and we'll help you do the best work of your life. If you join our team, you'll research, design, develop, debug, and support location estimation software. You'll also collaborate to qualify performance and support commercialization for hundreds of millions of users on multiple hardware families. You'll work with customers of location, both internal and external, to make best use of your work to support their applications. Minimum Qualifications: Graduate degree in Engineering, Computer Science or a related field or a Bachelor's degree with equivalent experience in positioning and Bayesian estimation. Proficient in Bayesian estimation concepts and Kalman filtering

Epidemiology Specialist - Freelance AI Trainer Project United States of America Are you a master of epidemiology eager to shape the future of AI? Large‑scale language models are evolving from clever chatbots into powerful engines of scientific discovery. With high‑quality training data, tomorrow's AI can democratize world‑class education, accelerate public health insights, and support evidence-based decision-making across the globe. That training data begins with you-we need your expertise to help power the next generation of AI. We're looking for epidemiology specialists who live and breathe study design, disease surveillance, outbreak investigation, biostatistics, risk factor analysis, transmission dynamics, public health interventions, and evidence synthesis. You'll challenge advanced language models on topics like cohort and case-control studies, incidence and prevalence, R₀ and herd immunity, confounding and bias, causal inference, diagnostic test performance, and global health surveillance systems-documenting every failure mode so we can harden model reasoning. On a typical day, you will converse with the model on real-world epidemiological problems and theoretical scenarios, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improvements to our prompt engineering and evaluation metrics. A PhD degree in epidemiology, public health, biostatistics, or a closely related field is ideal; peer‑reviewed publications, applied research in population health, or work in public health agencies or field epidemiology signal fit. Clear, metacognitive communication-“showing your work”-is essential. Ready to turn your epidemiology expertise into the knowledge base for tomorrow's AI? Apply today and start teaching the model that will teach the world. We offer a pay range