Deepgram jobs

Research Engineer, Pretraining, DeepMind New York, NY, USA At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $253000 (USD) + 15% bonus target + bonus + equity + benefits Learn more about benefits at Google . Focus on

Pretraining codebase SWE, DeepMind Mountain View, CA, USA At Google, research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority. We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $253000 (USD) + 15% bonus target + bonus + equity + benefits Learn more about benefits at Google . Enable day

Senior Technical Program Manager, Machine Learning Hardware, DeepMind Mountain View, CA, USA Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers. Using your extensive technical and leadership expertise, you manage projects of various size and scope, identifying future opportunities, improving processes and driving the technical directions of your programs. We are seeking a talented and highly motivated Machine Learning Hardware Program Manager to join our team. In this role, you will drive the program execution of our custom silicon portfolio, which spans both highly experimental research tracks and production-grade deployments. You will manage complex program life cycles across a hybrid ecosystem of internal engineering teams, cross-functional ML research collaborators, and silicon partners. You will work in close partnership with overall program leadership to ensure milestones are met, risk mitigation plans are executed, and seamless communication is maintained across all technical domains. Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI

Staff ML Engineer, Fine Tuning - Slack Washington - Seattle; Georgia - Atlanta; California - San Francisco *IN SCHOOL OR GRADUATED WITHIN THE LAST 12 MONTHS? PLEASE VISIT FUTURE FORCE FOR OPPORTUNITIES* Slack is looking for a Staff Machine Learning Engineer with deep expertise in model training and finetuning to join our ML team. You'll design, train, and ship NLP models that power core product experiences - from summarization and search ranking to generative AI features used by millions daily. This role is hands-on: you'll work at a low level with training frameworks, optimize model architectures, build finetuning pipelines, and own the full lifecycle from experiment to production. At Slack, that impact can be huge: We have over 10 million daily active users relying on our product. At peak usage, a million messages a minute pass through Slack. During the week, our users spend over a billion minutes a day active in our product. Machine learning engineers at Slack ship models that serve millions of users daily. This role owns that end-to-end: finetuning models for Slack's NLP tasks and putting them into production with the rigor and reliability our users expect. We're not looking for someone who hands off a checkpoint - we want someone who sees it through to serving traffic. Broader ML skills - data pipelines, experimentation, feature engineering - are valuable here too, but deep training and productionization expertise is the core of this role. This is a practical machine learning team, not a research team. Our

Machine Learning Engineer, CreativeX New York, New York, USA The CreativeX RAPID (Real-time Ad Personalization & Insights Development) team is seeking passionate and talented Machine Learning Engineer to join us. CreativeX is on a mission to enable brands of all sizes and categories to create, serve, measure, and optimize creative content with ease. Our team is responsible for tailoring the visual experience of ads to each context in real-time, leveraging nouvelle technologies such as latent diffusion models, large language models (LLM), reinforced learning (RL), computer vision, and related methods. Our mission is to provide engaging, dynamically optimized creatives with low latencies both on and off Amazon for self-service brand advertisers. We automate the customization of product creatives with real-time catalog data while providing advertisers with the flexibility to customize their creatives according to their preferences. Key job responsibilities - Quickly acquire knowledge of nouvelle technologies in Generative AI to solve complex problems in the Dynamic Creative Optimization (DCO) domain. - Investigate design approaches, prototype new technologies, and evaluate their technical feasibility, such as Auto ML, real-time ML serving systems. - Collaborate with scientists to design and build data pipelines for processing massive datasets and scaling machine learning models. - Develop and maintain platforms for developing, evaluating, and deploying machine learning models for real-world applications. Basic Qualifications: - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least

Machine Learning - Compiler Engineer , AWS Neuron, Annapurna Labs Cupertino, California, USA Do you want to be part of AI revolution? At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to AI hardware and software infrastructure. In order to deliver on that vision, we've created innovative software and hardware solutions that make it possible. AWS Neuron is the SDK that optimizes the performance of complex ML models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads. This role is for a software engineer in the Compiler team for AWS Neuron. As part of this role, you will be responsible for building next generation Neuron compiler which transforms ML models written in ML frameworks (e.g, PyTorch, TensorFlow, and JAX) to be deployed AWS Inferentia and Trainium based servers in the Amazon cloud. You will be responsible for solving hard compiler optimization problems to achieve optimum performance for variety of ML model families including massive scale large language models like Llama, Deepseek, and beyond as well as stable diffusion, vision transformers and multi-model models. You will be required to understand how these models work inside-out to make informed decisions on how to best coax the compiler to generate optimal implementation instruction. You will leverage your technical communications skill to partner with internal and external customers/stakeholders and will be involved in pre-silicon design, bringing new products/features to market, ultimately, making Neuron compiler highly performant and easy-to-use. Experience in object-oriented

Machine Learning Engineer - Evergreen Bucharest posted: Posted 30+ Days Ago

Machine Learning Engineer, AWS Neuron Inference, Annapurna ML Seattle, Washington, USA AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trn2 and future Trn3 servers that use them. This role is for a software engineer in the Machine Learning Applications (ML Apps) team for AWS Neuron. This role develops, enables and performance tunes building blocks for all key ML model families, including Llama3, GPT OSS, Qwen3, DeepSeek and beyond. The Neuron Inference Technology team works side by side with the Inference Model Enablement, compiler runtime engineers to create, build and tune high-performance distributed inference solutions for the latest generation Trainium accelerators. Experience optimizing LLM inference performance with kernels, Python, PyTorch or JAX is a must. Key job responsibilities This team develops optimized building blocks for the Neuron distributed inference library, tuning them to ensure highest performance and maximize efficiency running on Trn2 and Trn3 servers. A day in the life As you develop technology components, you'll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You'll also participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally with teams across Neufon in a fast-paced startup-like development environment, where we constantly stay on top of the latest priorities as the AI landscape evolves. About the team Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an

ML Compiler Engineer II - Neuron Kernel Interface , Annapurna Labs Seattle, Washington, USA The AWS Neuron Compiler team is actively seeking skilled compiler engineers to join our efforts in developing a state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI. Key job responsibilities As a ML Compiler Engineer II on the Neuron Compiler Automated Reasoning Group, you will develop and maintain tooling for best-in-class technology for raising the bar of the Neuron Compiler's accuracy and reliability. You will help lead the efforts building fuzzers and specification synthesis tooling for our LLVM-based compiler. You will work in a team with a science focus, and strive to push what we do to the edge of what is known, to best deliver our customers. Strong software development skills using C++/Python are critical to this role. A science background in compiler development is strongly preferred. A background in Machine Learning and AI accelerators is preferred, but not required. In order to be considered for this role, candidates must be currently located or willing to relocate to Seattle (Preferred), Cupertino, Austin, or Toronto. Basic Qualifications: - 3+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing

Machine Learning Engineer India - Hyderabad posted: Posted 7 Days Ago

Associate Machine Learning Engineer India - Hyderabad posted: Posted 7 Days Ago

Machine Learning Engineer India - Hyderabad posted: Posted 30+ Days Ago

Machine Learning Engineer - 5 Bangalore posted: Posted 30+ Days Ago

Sr Machine Learning Engineer India - Hyderabad posted: Posted 30+ Days Ago

Associate Machine Learning Engineer India - Hyderabad posted: Posted 30+ Days Ago

Machine Learning Engineer - 3 Bangalore posted: Posted 30+ Days Ago

Software Development Engineer - AI/ML, Amazon Neuron, Multimodal Inference Seattle, Washington, USA The Annapurna Labs team at Amazonbuilds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference and training performance. The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for AWS's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. As part of the broader Neuron organization, our team works across multiple technology layers - from frameworks and kernels and collaborate with compiler to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection

Principal Machine Learning Engineer India - Hyderabad posted: Posted 30+ Days Ago

Senior Machine Learning Engineer Vista, CA posted: Posted 29 Days Ago

2026 University Graduate - Machine Learning Engineer Seattle posted: Posted 30+ Days Ago

Senior Machine Learning Engineer United States - Remote posted: Posted 2 Days Ago

Senior Machine Learning Engineer San Jose posted: Posted 25 Days Ago

Machine Learning Engineer - Express Scripts Canada Mississauga, ON posted: Posted 30+ Days Ago

Machine Learning Engineer San Jose posted: Posted 7 Days Ago