Senior Staff Machine Learning Engineer, GenAI Platform Reddit IncSenior Staff Machine Learning Engineer, GenAI PlatformCA$292,500–$409,500 / yearWhat You'll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit's large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability.
Visual Intelligence and Machine Learning Research Scientist Apple IncVisual Intelligence and Machine Learning Research ScientistSan Jose, CAWe prototype algorithms from first principles all the way through to shipping features, working hand-in-hand with app teams and designers so that the science we build has immediate, tangible impact on how people interact with Apple products. Strong hands-on experience training and deploying deep learning models using modern frameworks (PyTorch, TensorFlow, JAX) and Python scientific libraries (NumPy, OpenCV, scikit-learn).
Machine Learning Architect - Conversational Speech Apple IncMachine Learning Architect - Conversational SpeechCupertino, CAOur mission is to build cutting-edge infrastructure, datasets, and models that empower Siri conversational AI, dictation, and speech-enabled Apple Intelligence features across natural language understanding, dialog generation, speech recognition, and multimodal interaction. You will evaluate emerging research and industry trends-including advances in large language models, multimodal architectures, and full-duplex natural conversational systems-and translate them into actionable roadmaps.
Machine Learning Scientist, Reinforcement Learning ProfluentMachine Learning Scientist, Reinforcement LearningEmeryville, CA$200,000–$330,000 / yearFounded in 2022 and headquartered in Emeryville, CA, Profluent is backed by leading investors including Altimeter Capital, Bezos Expeditions, Spark Capital, Insight Partners, Air Street Capital, AIX Ventures, and Convergent Ventures and has raised over $150M to date. PhD (or equivalent industry experience) in Computer Science, Machine Learning, Natural Language Processing, Applied Math, Computational Biology, Statistics, or a related field.
Machine Learning Engineer Pulse Software CorpMachine Learning EngineerSan Francisco, CAWe are a small, fast-growing team of engineers in San Francisco powering Fortune 100 enterprises, YC startups, public investment firms, and growth-stage companies. We have a breakthrough approach to document understanding that combines intelligent schema mapping with fine-tuned extraction models where legacy OCR and other parsing tools consistently fail.
Senior Machine Learning Engineer Strava IncSenior Machine Learning EngineerSan Francisco, CABuild from a rich dataset: Explore and use Strava's extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features. Analyzing the Data: Work closely with product managers, data scientists, and engineers to find opportunities for applying machine learning to drive business impact and enhance Strava's features and measure impact.
Senior Software Engineer - Machine Learning Infrastructure ATOMSSenior Software Engineer - Machine Learning InfrastructureSan Francisco, California$176,000–$230,000 / yearBuild and maintain software and tools for classical ML stack which helps data scientists manage full training lifecycle from data collection, data preparation, training, deployment and model serving. Our work only matters if it serves others, and we know that meaningful progress depends on the trust of the people we serve and the strength of our team—so we invest in both, creating an environment where you can do your best work and grow.
New(General Hire) Machine Learning Engineer (all levels) , TikTok Recommendation TikTok Inc(General Hire) Machine Learning Engineer (all levels) , TikTok RecommendationSan Jose, CACollaborate with cross functional teams to design product strategies and build solutions to grow TikTok in the US market. Experience building machine learning systems using frameworks such as PyTorch or TensorFlow.
NewMachine Learning Research Scientist, Post-Training Scale AI, Inc.Machine Learning Research Scientist, Post-TrainingSan Francisco, CA$180,600–$225,750 / yearThe range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact.
Software Engineering Lead, Machine Learning EmaSoftware Engineering Lead, Machine LearningSan Francisco Bay Area, CA$200,000–$270,000 / yearHeadquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production - we ship real systems that run real business processes at scale. You are someone who loves solving complex problems, enjoys the challenges of working with huge data sets, and has a knack for turning theoretical concepts into practical, scalable solutions.
Staff/Senior Machine Learning Research Engineer Scale AI, Inc.Staff/Senior Machine Learning Research EngineerSan Francisco, CA$227,200–$284,000 / yearResearch and prototype novel methods for agent performance improvement in a production/enterprise-ready setting - continuous learning loops, automated curriculum or data generation from production traces, online or offline RL - and validate them with rigorous experiments before they ship, making the call on where to build new infrastructure versus apply existing methods. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams.
Staff Machine Learning Engineer Primer.aiStaff Machine Learning EngineerSan Francisco, CAHands-on depth with LLMs and agentic systems (prompt and context engineering, tool use, retrieval and RAG) and the broader ML toolkit such as PyTorch, plus experience defining evals to measure and improve quality. Design and build the distributed, agentic systems behind our products at company-wide scale: tool-using conversational agents, multi-turn context, retrieval-grounded reasoning, and the orchestration that ties them together.
Staff Machine Learning Engineer - ML Training Infrastructure General Motors CoStaff Machine Learning Engineer - ML Training InfrastructureSunnyvale, CA$185,000–$335,300 / yearAs a Staff ML Engineer, you will operate as a technical leader across initiatives, partnering closely with machine learning engineers, research scientists, and platform teams to shape architecture, drive major technical decisions, and deliver state-of-the-art AI infrastructure that enables the future of intelligent driving technologies across General Motors vehicles. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
Physics Informed Machine Learning Scientist ASMLPhysics Informed Machine Learning ScientistSan Diego, CaliforniaThe Physics Informed Machine Learning Scientist works on the Virtual Source team building integrated master-model frameworks to capture the tightly coupled, multi-physics behavior of the system—enabling system-level optimization, reducing uncertainty in future source configurations, and guiding early technology decisions. Experience solving complex, open-ended modeling problems using optimization and deep learning methodologies, with strong expertise in data management and building scalable data and training pipelines for end-to-end model development and training.
Technical Producer II - League Studio, Machine Learning Riot Games IncTechnical Producer II - League Studio, Machine LearningLos Angeles, CAYou will set team direction to ensure project objectives are met, manage the day-to-day work, be the custodian of delivery processes internal to the team, and ensure that collaboration with external teams runs smoothly. Partner with Machine Learning Engineering Lead and Product lead to resource projects, monitor team health, and align on team composition, ensuring the team is set up to deliver against priorities successfully.
NewMachine Learning PhD Student, Frontier AI Evaluation (Contract) CobaltMachine Learning PhD Student, Frontier AI Evaluation (Contract)San Mateo, CADemonstrated depth in at least one area, for example optimization, reinforcement learning, language model training and post-training, learning theory, probabilistic methods, computer vision, natural language processing, or systems for ML. \n This opportunity is suited to students who are actively doing ML research: designing and running experiments, training and evaluating models, working through derivations, and debugging results that do not behave as expected.
NewResearch Engineer, Learnable Planner (Integration) WaabiResearch Engineer, Learnable Planner (Integration)San Francisco, CA$159,000–$296,000 / yearIntegrate cutting-edge ML models in production planning stack from development to validation, deployment, and monitoring - Develop necessary interfaces and pipelines in simulation for testing prototype or production planning models - Work closely with motion planning sub-teams and research scientists to improve our planner architecture and develop rich and novel representations that can facilitate end-to-end solutions - Champion engineering excellence, ensuring high-quality, well structured and tested code. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way.
Machine Learning Engineer, Factory Vision Systems Tesla IncMachine Learning Engineer, Factory Vision SystemsFremont, CADesign develop and implement computer vision and machine learning models for factory and warehouse applications including defect detection visual inspection process monitoring and quality assurance using techniques like object detection segmentation and anomaly detection. Work with diverse heterogeneous datasets combining multiple modalities including images multi-spectral sensor outputs video text and tabular data to build scalable solutions.
Head of Machine Learning – Remote Glint Tech Solutions LLCHead of Machine Learning – RemoteSunnyvale, CARemote$210,000–$250,000 / yearYou'll lead a high-performing ML team while remaining technically credible, partnering closely with Product, Engineering, and Executive Leadership to develop production-grade machine learning systems that directly impact the business. This is a highly visible leadership role responsible for building and scaling the next generation of fraud detection and risk decisioning products.
Machine Learning Engineer II, Applied Research Science Pinterest IncMachine Learning Engineer II, Applied Research ScienceSan Francisco, CARemoteWhat you'll do: Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems Collect, analyze, and synthesize findings from data and build intelligent data-driven model Write clean, efficient, and sustainable code Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search Scope and independently solve moderately complex problems. Youll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: computer vision, graph neural network, natural language processing (NLP), inclusive AI, reinforcement learning, user modeling, and recommender systems.