305 ml research engineer jobs at 82 companies in Soquel, CA
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ML Research Engineer
Cupertino, California, United States
OnsiteFull Time
AppleNASDAQ: AAPL: Designs and sells consumer electronics, software, and online services.
Experience across the full ML lifecycle including training infrastructure, performance optimization, data pipelines, and production deployment to support next-generation video technology.
Clera: AI talent agent matching professionals with high-growth startup roles
3+ YOE3+ years ML research/applied ML experience; proficiency in Python and ML frameworks (PyTorch,JAX,TensorFlow); experience with Transformers, diffusion models, RLHF; building scalable experimentation pipelines; strong documentation and reproducibility skills.
Senior AI/ML Research Engineer – Model development
Sunnyvale, California, United States
$167k-$283k/yrOnsiteFull Time
IntuitiveNASDAQ: ISRG: Robotic-assisted systems for minimally invasive surgery.
5+ YOEMS or PhD in CS/EE/Robotics, 5+ years applied AI/ML research experience; experience training/fine-tuning multimodal/foundation models, simulation-to-real workflows, and strong Python/C++ and PyTorch/TensorFlow/JAX skills.
ML Systems Research Engineer, RL / Inference / Agent Systems
Santa Clara, California, United States
HybridFull Time
AMDNASDAQ: AMD: Designs and manufactures computer processors and graphics technology.
Experienced ML systems engineer with strong Python and ML framework skills, experience in RL/inference systems, distributed experimentation, and GPU/infrastructure workflows; advanced degree preferred.
Python, PyTorch, JAX, TensorFlow, Kubernetes, Ray, Slurm, ROCm, HIP, CUDA
TikTok: Global short-form video hosting and social media platform.
BS/MS in quantitative field, research or industry experience in ML/DL/statistics, proficient in C/C++ and Python, familiar with TensorFlow/PyTorch/MXNet, Hadoop and Spark, experience with LLM/RL preferred.
DatologyAI: Automated data curation for efficient AI model training.
4+ YOEBachelor's or equivalent, 4+ years research lab experience, strong ML systems and distributed training background, software engineering and empirical research skills; PhD preferred; publication/open-source contributions valued.
Hewlett Packard EnterpriseNYSE: HPE: Provides edge-to-cloud IT infrastructure and platform services.
PhD in CS/EE or related with strong ML research background, expertise in LLMs and reinforcement learning, proficiency in PyTorch and Python, GPU/system optimization experience, strong publication record and mentoring ability.
3+ YOEBachelor's in CS or related,3+ years software/ML engineering or ML research,experience with research teams and large-model training,strong communication and critical thinking.
MetaNASDAQ: META: Develops social networking platforms and virtual reality technologies.
4+ YOEBachelor's in CS/CE or equivalent; 4+ years in ML engineering/research; Python and PyTorch; independent feature design; strong software practices; adaptable.
AdobeNASDAQ: ADBE: Provides software for digital media creation and marketing analytics
Experience building large-scale audio/video data pipelines, strong audio domain knowledge, generative-ML research experience, data acquisition/licensing and evaluation skills, and excellent communication.
WindBorne Systems: Operates smart weather balloons to provide global atmospheric data.
Strong ML research and engineering skills with Python and PyTorch, experience with large messy datasets, research taste, and ability to convert experiments into reusable systems.
ArcherNYSE: ACHR: Develops electric vertical takeoff and landing aircraft for urban mobility.
MS or PhD in CS or Computer Engineering with strong emphasis on AI/ML; strong ML frameworks; Transformer and multimodal models expertise; production-ready research experience.
QualysNASDAQ: QLYS: Provides cloud-based platform for cybersecurity and compliance management.
6+ YOE6+ years combined software/ML and security research or penetration testing experience; strong Python; experience with Scikit-learn, TensorFlow or PyTorch, LangChain/LlamaIndex, vector DBs (FAISS, Pinecone, Qdrant), cloud (AWS/GCP/Azure), SQL and Pandas.
Rhoda AI: Developing generalist robotic intelligence for real-world industrial automation.
Strong software engineering with MLOps or ML platform experience; distributed training frameworks; experiment tracking and artifact management; GPU cluster management; reliability engineering.
Hewlett Packard EnterpriseNYSE: HPE: Providing global edge-to-cloud infrastructure and IT solutions for businesses.
PhD in CS/EE or related, extensive LLM and RL research experience, strong Python and PyTorch skills, experience with GPU acceleration and model optimization, publishing and prototyping background.
Bosch: Global manufacturer of automotive and industrial engineering technology.
Bachelor's degree in CS/engineering, strong Python software engineering, hands-on experience with LLMs and agentic systems (tool use, planner-executor, RAG), ML fundamentals, experiment design, and strong communication skills; industrial research experience preferred.
Fireworks AI: High-performance inference platform for deploying generative AI models.
Strong programming (Python, C++, or Rust); deep ML framework knowledge (PyTorch, JAX, TensorFlow); experience with distributed systems (CUDA, NCCL, MPI); strong math foundation and track record implementing deep learning algorithms.
NVIDIANASDAQ: NVDA: Designs GPU-accelerated computing and artificial intelligence hardware.
8+ YOEMS/PhD in CS/CE or equivalent experience, 8+ years in computer vision/video retrieval/ML, experience with agentic AI workflows, model training/optimization, PyTorch and Python, strong communication and research familiarity.
Fireworks AI: Provides high-performance generative AI model inference and deployment infrastructure.
Strong programming (Python/C++/Rust), ML framework experience (PyTorch/JAX/TensorFlow), distributed systems experience (CUDA/NCCL/MPI), strong math background, and track record implementing deep learning algorithms.
Inflection AI: Develops human-centered personal AI and large language models.
2+ YOE2-5 years in audio/speech or multimodal ML; PyTorch; large-scale neural models; audio fundamentals; production-ready training and CUDA; diffusion models; strong communication; BS in CS/EE/linguistics; MS/PhD preferred.