21 applied machine learning engineer jobs at 20 companies in Cotati, CA
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Applied Machine Learning Engineer
San Francisco, California, United States
HybridFull Time
Ohm: Enterprise AI platform for hardware and battery product development.
3+ YOE3+ years in data science or applied ML; experience delivering production ML systems, working with time-series/noisy engineering data, anomaly detection/optimization, and cloud deployment/support; STEM background.
Shipt: Provides same-day delivery services from local retailers via app.
4+ YOE4+ years applying machine learning and statistics in industry, Python development, experiment design and analysis, presenting to stakeholders; MS/PhD preferred.
Mercor: Connecting expert human intelligence with frontier AI model development.
Experience shipping ML systems; expertise in ranking, recommendation, search, or matching; comfortable across applied ML stack (data, features, training, inference); strong engineering fundamentals and product impact focus.
Atoms: Building specialized industrial robots and physical AI systems.
10+ YOE10+ years MLE experience; deep expertise applying transformers to robotics/spatio-temporal data; multimodal, sensor-fusion, and model optimization experience; proficiency in PyTorch or JAX, Python, and C++.
AfterQuery: Curating specialized datasets and environments to train frontier AI models.
3+ YOE3–6 years relevant experience; strong software engineering and applied ML background; experience shipping production systems and working with messy real-world data; strong data intuition and cross-team collaboration skills.
PinterestNYSE: PINS: Visual discovery engine for finding inspiration and creative ideas.
6+ YOEMS/PhD in CS/ML/NLP/Statistics/Information Sciences,6+ years industry experience,ML/IR research experience,mastery of Java,C++,Python or ML frameworks (Tensorflow,Pytorch,MLFlow),strong communication and problem-solving skills.
Stand: Provides homeowners insurance using physics-driven AI risk assessment.
Deep experience designing and productionizing multimodal ML and LLM systems, applying ML to physical systems, strong ownership, communication, and cross-disciplinary collaboration.
Glean: AI platform for enterprise search and automated workplace agents
2+ YOE2+ years industry ML or applied AI experience, production ML ownership, LLM/NLP/search experience, strong coding in Python/Go/Java/C++, experimentation and evaluation skills.
Senior / Staff Machine Learning Engineer, Applied AI
Cambridge or San Francisco
$180k-$336k/yrOnsiteFull Time
Lila Sciences: Develops an AI platform for autonomous scientific research and discovery.
Strong ML engineering with LLM experience; expertise in training, adapting, evaluating, and deploying models; proficiency in Python and modern ML frameworks; ability to design experiments and debug model behavior.
Python, PyTorch, JAX, TensorFlow, Megatron-LM, TorchTitan, DeepSpeed, Ray
Waymo: Autonomous driving technology for ride-hailing and logistics.
5+ YOEBachelor's/Master's/PhD in CS/ML/robotics, 5+ years ML engineering/applied deep learning experience, proficiency in Python and JAX/Flax/PyTorch, and experience designing evaluation frameworks.
Mistral AI: Developing frontier artificial intelligence models and enterprise AI solutions.
2+ YOEPhD or master in AI/data science,2+ years technical experience,LLM fine-tuning and RAG/agent experience,API and product deployment,Python and PyTorch proficiency,strong communication;fluent English.
Scale AI: Provides data and infrastructure for training artificial intelligence models.
5+ YOE5+ years as an ML engineer or applied scientist with production ML/LLM systems; experience building evaluation/monitoring or continuous-learning infrastructure; strong experimentation and collaboration skills.
The Walt Disney CompanyNYSE: DIS: Produces movies, operates theme parks, and provides streaming services.
7+ YOE7+ years building and deploying ML models, strong background in recommender systems, applied ML/AI/LLM experience, proficiency with PyTorch, TensorFlow, Databricks, Spark, and SQL, strong communication skills.
Principal Machine Learning Engineer (Reconstruction / Quantitative Imaging)
San Francisco, California, United States
OnsiteFull Time
Midjourney: Independent research lab developing generative AI and medical imaging technology.
Strong applied ML experience with imaging or signal processing, ability to move between research prototypes and production systems, strong evaluation discipline, and experience applying ML to physics-based/inverse problems.
Discord: A platform providing voice, video, and text communication services.
5+ YOE5+ years ML engineering experience, 3+ years in Ads ML; strong Python skills; experience with PyTorch or TensorFlow; applied deep learning and real-time inference experience; A/B testing and ML evaluation skills.
Omnifold: AI-powered forecasting and planning platform for supply chains.
Technical sales/consulting or forward-deployed engineering experience, background in data science or machine learning, experience with enterprise sales cycles, strong project management and communication, proficiency in Python and SQL.
Taste Labs: Building the data and infrastructure layer for AI taste.
Experienced with LLMs, post-training and evaluation design (judges/reward models), running ML experiments and infra, collaborating with external labs, and publishing results.
Cartesia: Builds real-time generative voice and multimodal AI models.
Experience in machine learning, generative model training/debugging (SFT, RL), large multilingual dataset construction, software engineering, and evaluation design.
AppleNASDAQ: AAPL: Designs and sells consumer electronics, software, and online services.
Apply computer vision, image processing, and machine learning to tune still image quality and understand user behavior; passion for photography and shipping product experiences at scale.
Postdoctoral Scholar in Bay Area, California, United States
Berkeley, California, United States
$69k-$107k/yrOnsiteFull Time
Lawrence Berkeley National Laboratory: Conducts multidisciplinary scientific research for the U.S. Department of Energy.
PhD in Chemistry, Materials Science, Computational Science, Data Science, Applied Mathematics, Physics, Chemical Engineering or related field; experience with thermodynamics, calorimetry, atomistic simulations, and machine learning modeling; proficient in Python/C++.