Data Science & Machine Learning Jobs

As MLRE on the Data Foundation team, you’ll work on cutting edge research to define the data flywheel that makes the whole machine move. Build synthetic data pipelines to generate enterprise environments to use for RL post-training. Any information we collect in connection with your application wi

Leverage millions of miles of driving data and interventions to build a robust and scalable end-to-end learning based self-driving system Use cutting-edge techniques from generative modeling, imitation learning, and reinforcement learning to improve the planning and reasoning capabilities of our dri

The project scientist will make significant and creative contributions in the area of machine learning & data analytics. Expertise in databases, data infrastructure, data governance. Develop machine learning approaches, computer vision tools to help pre-process dataset and annotations to generate gr

PhD new grads or MS grads with 1-3 years of experience in applied machine learning, familiar with one or more algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep, etc. Pr

Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA. Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA. Integrate with vector/feature stores and data pipelines (FAISS/Milvus/Pine

The role involves working on data pipelines, collaborating with DevOps and data teams, and improving existing systems. A leading networking technology company in Santa Clara is seeking a Data DevOps Engineer with 8+ years of experience to join their ML/AI team.

Hive) Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models, as well as integrating to product use cases. Staff Machine Learning Engineer, Listings and Host Tools Data and AI. Strong programming (Scala / Python / Java/ C++

The ideal candidate will work collaboratively with experimental biologists and machine learning engineers, contributing to cutting-edge projects with significant scientific impact. A leading research organization in Palo Alto is seeking an experienced Machine Learning Research Scientist to develop l

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. We believe massive scale th

Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience. Experience with state-of-the-art control systems, reinforcement learning algorithms. Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

The ideal candidate will have a strong background in machine learning and a passion for developing innovative solutions.

Applied Machine Learning Engineer, Circuit Design - New College Grad 2026 page is loaded## Applied Machine Learning Engineer, Circuit Design - New College Grad 2026locations:. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting

Machine Learning Data Scientists. Ability to use Python/PySpark for exploratory data analysis and modeling. Work closely with ML teams to design algorithms and uncover opportunities to improve ranking and personalization.

As an ASIC Design Verification Engineer, you will use design and verification expertise to verify complex digital designs. Plan the verification of complex digital design blocks by fully understanding the design specification and interacting with design engineers to identify important verification s

Tackle hard data problems: Work on classification problems with extreme class imbalance, sparse signals, and "cold start" label challenges. Establish ML infrastructure foundations: Partner with platform engineering team to design feature services, model training pipeline, model serving standards, an