Senior Machine Learning Engineer

This is a fully remote position, open to applicants in California.

📋 Description

• Design and enhance deep learning pipelines on distributed computing platforms for model training, data processing, model management, and inference.

• Work collaboratively with machine learning scientists and software engineers to ensure development pipelines meet both scientific objectives and operational requirements.

• Oversee, assess, and optimize deep learning model training pipelines to enhance performance and scalability.

• Create and uphold robust, reproducible deep learning pipelines.

• Enhance stack performance through profiling, optimization, benchmarking, caching, and debugging within distributed systems.

• Promote effective communication between engineering and scientific teams.

• Document and disseminate best practices to foster learning and continuous improvement.

⛳️ Requirements

• MS degree or equivalent experience in a relevant quantitative field such as Computer Science, Statistics, Mathematics, or Software Engineering, with a focus on AI/ML theory and/or practical implementation.

• Minimum of 5 years of post-MS industry experience in developing AI/ML software engineering pipelines.

• Proficiency in a general-purpose programming language such as Python, Java, Julia, C, or C++.

• Strong understanding of machine learning and deep learning principles.

• Practical experience with frameworks like PyTorch, TensorFlow, Jax, or Scikit-learn.

• Comprehensive knowledge of scalable and distributed computing platforms such as Ray or DeepSpeed.

• Experience with integrating ML developer tools such as TensorBoard, Wandb, or MLflow.

• Familiarity with AWS, Google Cloud, or Azure for deploying and managing AI/ML models and pipelines.

• Understanding of Docker and Kubernetes.

• Proven track record in developing and optimizing workflows for deep learning models, LLMs, or similar high-volume, high-complexity challenges.

• Experience in managing large datasets, including HDFS or Parquet on object storage, PyArrow, and Spark.

• Proficiency with Git and CI/CD practices.

• Expertise in building and launching large-scale ML frameworks within a scientific context.

• Ability to collaborate effectively with cross-functional teams and communicate across various disciplines.

🏝️ Benefits

• Equity

• Cash bonuses

• Full range of medical benefits

• Full range of financial benefits

• Other benefits depending on the position offered

• Equal-opportunity employer valuing diversity