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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. Proficiency in Python, C++,
Familiarity with deep learning frameworks: PyTorch (primary), TensorFlow. Data & storage: SQL/NoSQL, vector stores (FAISS/Milvus/Pinecone/pgvector), Parquet/Delta, object stores. Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA.
The ideal candidate will have demonstrated capability to deploy data science and machine learning models with large datasets in an industry setting. Comfortable querying and analyzing large datasets using tools such as SQL, Snowflake, or similar analytical data platforms. Strong data analysis skills
Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills Deep understanding of Machine Learning best practices (eg. Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), data warehouse (eg. Hive) Industry ex
Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related technical field - or equivalent practical experience. Direct experience with agentic systems, including tool use, environment design, or reinforcement learning. The vision for AIML FM Data organization is to improve Fou
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. Ex
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
Strong foundational knowledge in machine learning and deep learning algorithms. AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA. AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid
As a Machine Learning Data Platform Engineer, you'll design and build the scalable dataset management platform that enables teams across Apple to discover, curate, version, share, process, and consume ML datasets with enterprise-grade compliance and governance. Experience building data pipelines tha
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. Clear experiences with constructing high quality data to use to improve an LLM/Agent. You’ll also receive benefits including, but not limited to: Comprehensive
Proficient using data query languages (SQL and/or Spark/scala) to quickly build complex yet efficient data queries at scale and using Python to build production-quality code. The candidate will work alongside data ops partners, ML engineers, software developers, and data engineers to improve model p
Hands-on experience developing machine learning models using frameworks such as PyTorch or TensorFlow. We are seeking a Machine Learning Engineer with strong expertise in computer vision and large-scale data processing. Strong foundation in computer vision, including experience with deep learningbas
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Expertise in databases, data infrastructure, data governance. Develop machine learning approaches, computer vision tools to help pre-process dataset and annotations to generate groundtruth benchmarks. The project scientist will make significant and creative contributions in the area of machine learn
Machine Learning Data Scientists. Ability to use Python/PySpark for exploratory data analysis and modeling. Experience in modern deep learning architectures and probabilistic models.