Senior Machine Learning Engineer

MS or equivalent experience in a relevant, quantitative field (Computer Science, Statistics, Mathematics, Software Engineering) with an emphasis on AI/ML. 5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines. Proficiency in Python (preferred), Java, Julia, C, C++. Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks (PyTorch, TensorFlow, Jax, Scikit-learn). In-depth knowledge of scalable and distributed computing platforms (Ray, DeepSpeed) and their integration with ML developer tools (TensorBoard, Wandb, MLflow). Experience with cloud platforms (AWS, Google Cloud, Azure). Understanding of containerization technologies (Docker) and computing resource orchestration tools (Kubernetes). Proven track record of developing and optimizing workflows for training DL models. Experience managing large datasets, including data storage, retrieval, and efficient data processing. Proficiency in version control systems (Git) and CI/CD practices. Expertise in building and launching large-scale ML frameworks in a scientific environment.

Implement and refine DL pipelines on distributed computing platforms. Collaborate with ML scientists and software engineers. Monitor, evaluate, and optimize DL model training pipelines. Develop and maintain robust and reproducible DL pipelines. Drive performance improvements across the stack. Act as a bridge facilitating communication between engineering and scientific teams.