Thought Machine jobs

Core Banking developer Dublin, Ireland This role suits candidates with direct Thought Machine experience or a comparable background building digital banking products on modern core platforms, with strong engineering fundamentals and an app...

Director, Thought Leader Liaison (Neuro) Remote - United States posted: Posted 4 Days Ago

Associate Director, Thought Leader Liaison - Neurology (West) 3 Locations posted: Posted 4 Days Ago

Associate Director, Thought Leader Liaison - Neurology (Northeast) 6 Locations posted: Posted 4 Days Ago

Associate Director, Thought Leader Liaison - Neurology (Southeast) 3 Locations posted: Posted 4 Days Ago

AIML - Machine Learning and Applied Research, Responsible AI and Safety Cupertino, United States of America Apple Intelligence is designed as a deeply integrated, privacy-preserving capability that seamlessly enhances what people can do across iPhone, iPad, Mac, and other devices. Our goal is to elevate the user experience without requiring our customers to learn new products or fundamentally change how they interact with their technology. Our team leads Responsible AI & Safety initiatives for global generative AI products, operating at the intersection of policy, product, and GenAI. We're seeking candidates who will shape safety policies in partnership with leadership, design, engineering, legal, and regulatory stakeholders-ensuring our safeguards advance both user protection and product innovation. You will collaborate closely with top machine learning researchers and engineers, software engineers, and design teams to develop and deliver groundbreaking solutions for Apple products. We believe that the most exciting problems in machine learning research arise at the intersection of emerging technologies and real-world use cases. This is also where the most critical breakthroughs come from. You will also work on producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience. Minimum Qualifications: 3+ years of proven ability in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision 4+ Years research or product deployment record in areas

Machine Learning Scientist 4 - Content & Conversation Modeling Seattle,Washington,United States of America | Los Gatos,California,United States of America At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. The Content & Conversation Modeling team delivers high-leverage ML solutions using Netflix's unique media data, driving decisions across content strategy, acquisition, scheduling, and advertising. Our models are used to predict engagement, forecast title performance, assess catalog strength, and so much more. We are looking for a senior machine learning scientist to develop, optimize, and deploy scalable ML solutions that power content decisions at Netflix. In this role, you will: Innovate on a suite of predictive models to help inform our content strategy. Be a thought partner with our content strategy teams as we continue to evolve our approach to content valuation, scheduling, and performance. Partner closely with our analytics teams as they leverage our models on the ground both in the US and globally. Own the end-to-end ML model development lifecycle, from ideation and feature engineering, to model training, evaluation, deployment, monitoring, and continuous improvement. Inform and influence data and ML infrastructure development through partnership with data engineer, ML Ops, and ML Platform teams. Live Netflix values while bringing a new perspective

AIML - Sr Machine Learning Engineer, Responsible AI Cupertino, United States of America Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple's Generative-AI powered features and products. In this role you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple's Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models. This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology & infrastructure to benefit ongoing and future Apple Intelligence safety evaluations. Producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand

Software Machine Learning Engineer (Universal Robots, Bangalore - India) Software Machine Learning Engineer (Universal Robots, Bangalore - India) Our Purpose TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are supported to innovate and learn something new every day. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team - one that makes better decisions, drives innovation and delivers better business results. Opportunity Overview We are seeking a Software Engineer with AI/ML experience to join the AI Partnerships team in Bangalore, India. This mid-level role focuses on building, deploying, and maintaining the software systems and ML pipelines that connect advanced AI capabilities with Teradyne's robotics products and partner ecosystems. You will collaborate with machine learning researchers and robotics engineers to ensure that state-of-the-art AI models are delivered as robust, production-ready software for applications in robot manipulation, visual inspection, and autonomous mobile robots (AMRs) / mobile manipulators. This role emphasizes hands-on development, experimentation, and collaboration rather than technical leadership. You will own significant software modules end-to-end - from understanding the problem through designing, building, testing, and supporting them in production. Responsibilities Design and implement ML pipelines for training, evaluation, and de

Physical Design Engineer, Machine Learning San Jose, United States of America At Apple, we believe our products begin with our people. By hiring a diverse team, we drive creative thought. By giving that team everything they need, we drive innovation. By hiring incredible engineers, we drive precision. And through our collaborative process, we build memorable experiences for our customers! These elements come together to make Apple an amazing environment for motivated people to do the greatest work of their lives. You will become part of a hands-on development team that sets the standard in cultivating excellence, creativity and innovation. Come help us design the next generation of revolutionary Apple products. We are looking for a forward-thinking and unusually talented engineer. As a member of our dynamic group, you will have the rare and rewarding opportunity to craft and implement methodologies and solutions with a high impact on upcoming products that will delight and inspire millions of Apple's customers every single day. In this role, you will be directly involved in our physical design machine learning efforts, collaborating right alongside our internal multi-functional teams, and using your expertise in machine learning and physical design to ensure that our SOCs achieve the optimal Power, Performance, and Area (PPA). We account for every nano watt, every nano meter, and every pico second. As a member of the physical design machine learning architecture team, you will be part of a dynamic team that is building the most efficient application processors on the planet, powering

Thought Leader Liaison LEAD Nephrology Remote, USA posted: Posted 30+ Days Ago

Associate Director, Thought Leader Liaison - North Central 12 Locations posted: Posted 4 Days Ago

Machine Learning Engineer - Ads Relevance & Quality Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! Apple's Ads team is seeking a highly skilled and motivated Machine Learning Engineer to join the Ads Relevance and Quality team. This team is responsible for ensuring high-quality, trustworthy ad experiences by building intelligent systems to evaluate ad relevance, detect low-quality or offensive content, and optimize user satisfaction. You'll work at the intersection of applied ML, NLP, and content quality-designing models and systems that understand queries, flag inappropriate content, and raise the bar for ad relevance and user trust across billions of queries and impressions. You'll play a key role in shaping the future of safe, high-quality advertising at Apple. Your work will help ensure that ads remain useful, relevant, and respectful of our users-supporting Apple's values of privacy, trust, and transparency. You'll collaborate with world-class engineers and researchers, apply cutting-edge ML techniques in real-world systems, and have a direct impact on the

AIML - Senior Machine Learning Engineer - Data Science, Responsible AI and Safety Cupertino, United States of America Would you like to play a part in building the next generation of generative AI applications at Apple? We're looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple, our products, and the broader world. This role is directed at assessing, quantifying, and improving the safety and inclusivity of Apple's Generative-AI powered features and products. In this role you'll have the opportunity to tackle innovative problems in machine learning, particularly focused on large language models for text generation, diffusion models for image generation, and mixed model systems for multimodal applications. As a member of Apple's Responsible AI group you will be working on a wide array of new features and research in the generative AI space. Our team is currently interested in large generative models for vision and language, with particular interest on Responsible AI, safety, fairness, robustness, explainability, and uncertainty in models. This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally, this role researches and develops auto-grading methodology & infrastructure to benefit ongoing and future Apple Intelligence safety evaluations. Producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance;

Senior Machine Learning Engineer, GAI Search Platform - Moveworks Mountain View, CALIFORNIA, United States Company Description: It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today - ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description: What You Will Do We are looking for senior/staff engineers to join our GenAI Search Platform team to improve our search-based question answering systems, utilizing both traditional machine learning and cutting-edge generative AI technologies. At Moveworks, we build conversational search systems to provide instant answers to enterprise users' questions. We deliver business intelligence support by combining modern information retrieval with the latest advancement in natural language understanding, including LLMs (large language models). By accurately retrieving, matching, ranking, and summarizing text snippets grounded in heterogeneous knowledge sources, our search products are reshaping the enterprise search experience for millions of our customers' employees. For the Search Platform , we are looking for passionate leaders who can provide technical direction and thoughtful coaching to our team of search and machine-learning engineers. The search platform team works closely with the

Senior Thought Leader Liaison, Lung - Atlanta Region 8 Locations posted: Posted 30+ Days Ago

Associate Director, Thought Leader Liaison - Northeast 6 Locations posted: Posted 4 Days Ago

Senior Machine Learning Engineer – Ads Predictions Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! We're is looking for a highly skilled and motivated Machine Learning Engineer to join our Predictions group. We build the core machine learning models that power ad predictions and monetization across Apple's App Store and News platforms. The ideal candidate will bring deep expertise in machine learning, information retrieval, and large-scale modeling, and will thrive in a fast-paced, privacy-first environment. You'll work at the intersection of applied ML, deep learning, and retrieval systems-developing models that predict user interaction, optimize marketplace outcomes, and scale across billions of queries. You'll also explore and operationalize emerging techniques in Large Language Models (LLMs), Reinforcement Learning, and representation learning to advance Apple's ad prediction systems. Design and implement ML models to improve predictions of user interaction, click-through rate (CTR), and conversion rate (CVR) Develop and optimize retrieval algorithms, leveraging techniques from classical IR and modern deep learning Contribute to

Senior Machine Learning Engineer - Matching, Apple Ads Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone! You'll have the opportunity to develop models that improve our platform across the board, write production code to generate recommendations, work closely with business partners to help drive the development of new products as well as perform large scale and complex experiments to understand their effects. You'll drive strategic outcomes through substantial innovation in multiple fields by leading the development and application of advanced techniques and algorithms to improve our ad network. You've, or will develop a deep understanding of the ad network behavior, and will work with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You'll lead the conception, development, and delivery of state of the art capabilities that differentiate our products and are core to our business. You should have experience developing and implementing machine learning algorithms, ideally within the ads space. You'll have an

Senior Machine Learning Engineer - Ads Auction Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. We are seeking a self-motivated individual that will build out the next generation of our ads platforms and ensure that Apple provides the most relevant and high quality ads experience while maintaining a healthy marketplace. The ideal candidate has a strong background in auction theory, applied machine learning, and large-scale systems, along with hands-on experience building and optimizing auction-based ad delivery systems in production. You will have an excellent understanding of scalable architectures and thrive working in Agile environments. In this role, you are responsible for designing the core auction system that powers our advertising platform to drive optimal outcomes for advertisers, users, and our platform. You will have the opportunity to build the next generation solutions for marketplace optimization that enable driving optimal value for multiple stakeholders in the system. You will have the opportunity to apply your ability to move the state

Software Machine Learning Engineer North Reading, MA Our Purpose TERADYNE, where experience meets innovation and driving excellence in every connection. We are fueled by creativity and diversity of thought and in our workforce. Our employees are supported to innovate and learn something new every day. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team - one that makes better decisions, drives innovation and delivers better business results. Opportunity Overview As a Machine Learning Engineer, you will design, develop, and deploy applied AI solutions with a good knowledge on graph machine learning, reinforcement learning, and interpretable AI. You will work closely with cross-functional teams to build scalable ML systems that model complex relationships in engineering data, optimize decision-making processes, and provide transparent, explainable insights. This role emphasizes hands-on development, experimentation, and collaboration rather than technical leadership. Design and implement pipelines for training, evaluation, and deployment of ML models. Apply graph ML methods to model relationships in structured and unstructured data. Build and experiment with reinforcement learning algorithms (e.g., policy gradients, PPO, Q-learning) for optimization and decision-making tasks. Incorporate interpretability and explainability techniques (e.g., SHAP, LIME, attention-based methods) into ML systems. Collabor

Staff Machine Learning Engineer – Ads Platform Austin, United States of America At Apple, we focus deeply on the customer experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, MLS Season Pass and now F1 ! . Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to news publishers to big, global brands. Because when advertising is done right, it benefits everyone. Apple Ads is Hiring a hands-on Machine Learning Engineer. In this role you will build design and build Machine learning systems and data pipelines to safeguard the advertiser trust of our platform and enhance invalid traffic protections. You will define and execute an innovation roadmap; build and deploy models with robust CI/CD, feature stores, and streaming infrastructure (e.g., Kafka/Spark/Flink); and run A/B experimentation. You will lead performance tuning, calibration, and drift detection to deliver measurable improvements in product quality, user experience, latency, and cost. Develop and manage end-to-end lifecycle of machine learning models, including observability for large-scale, high-throughput, and low-latency production systems. Design, develop, and optimize distributed algorithms and data processing frameworks(e.g., Spark). Implement scalable feature pipelines to ingest, clean, transform, and analyze massive datasets. Reinforce Ads integrity and advertiser trust by safeguarding infrastructure. Solve complex problems

Senior Machine Learning Engineer - Ads Bidding & Pacing Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. We are seeking a self-motivated individual that will build out the next generation of our ads platforms and ensure that Apple provides the most relevant and high quality ads experience while maintaining a healthy marketplace. You should have experience developing and implementing machine learning or optimization algorithms, ideally within the ads space, recommendations, or search relevance. You will have an excellent understanding of scalable architectures and thrive working in Agile environments. In this role, you will design and build scalable solutions that enable advertisers to optimize for their campaign goals and performance on the Apple Ads. You will have the opportunity to build the next generation solutions for budget and bid optimization that enable driving optimal campaign performance and advertiser experience. You will have the opportunity to apply your ability to move the state of the art techniques in a fast growing

Senior Machine Learning Engineering Manager – Ads Predictions Cupertino, United States of America At Apple, we focus deeply on our customers' experience. Apple Ads brings this same approach to advertising, helping people find exactly what they're looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. We are looking for a leader with deep experience in Ad Tech who has built and scaled complex machine learning models in production. Preferably, you have a strong track record of delivering high-impact response prediction systems (e.g., click-through rate, conversion rate, post-conversion optimization) at scale, and understand the nuances of optimizing for user engagement, relevance, and long-term value under latency constraints. You bring hands-on experience developing and deploying large-scale models, with an appetite for pushing state-of-the-art techniques and advancing model capability through increased scale and complexity. You are motivated by privacy-preserving machine learning and have experience building systems that operate effectively within privacy-first constraints. In this role, you will lead the strategy and development of inference models that predict and optimize user interactions with ads, working across the full modeling stack-from data and model training pipelines to real-time serving and experimentation. You will