Sr. Machine Learning Engineer

Boston, MA             ·            Full time

Sr. Machine Learning Engineer

• Boston, MA
• Full Time
• Experienced

We are a rapidly growing Series-C, Boston-based medical technology company applying machine intelligence to medical imaging to help clinicians make more informed decisions on cardiovascular care – leading to better patient outcomes, improved quality of care, and reduced healthcare costs. Come work at Elucid and be part of delivering on our mission to prevent heart attacks and strokes.

Join our growing Deep Learning team! As a Sr. Machine Learning Engineer, you’ll be helping to implement the team’s models (including your own!) on our powerful GPU cluster and in the cloud, creating and optimizing deep learning models, and collaborating with our clinical team to ensure data quality and model validity. You will work with modern DL techniques including self and semi-supervised learning, transformers, foundation models and advanced hyperparameter search, as well as frameworks like PyTorch and platforms including Azure OpenAI and AWS.

This is an ideal role for candidates with experience in biomedical image understanding and an interest in ML/DL for healthcare.

While candidates in the Boston, MA area are preferred, we are accepting applications from candidates in the continental US with a strong Preference for eastern time zones.

Responsibilities:

• Work with a high-performing team of ML and ML Research Engineers to integrate deep learning models into a production environment.
• Help build and improve upon our data pipeline, including writing data curation algorithms and data loaders.
• Collaborate with clinical team members to ensure data quality and model validity.
• Create, test, and optimize deep learning models.

Required Experience:

• Master’s degree in machine learning, computer science, mathematics, statistics or related quantitative field.
• 6+ years overall experience developing ML algorithms; including 4+ years in industry, preferably in the computer vision or biomedical image understanding space.
• 2+ years of Python experience and familiarity with Python-based deep learning frameworks (ideally PyTorch).
• Experience with git and modern software development methodologies, as well as a demonstrated ability to manage projects from start to finish.
• Basic AWS experience (EC2, S3, etc.).
• Experience with modern MLOps tools like Weights & Biases, MLFlow, Neptune, etc.
• Experience with some of: DevOps tools for CI/CD (Jenkins, Github actions), containerization tools (e.g., Docker, Kubernetes), and tools for deploying production ML models (e.g., NVIDIA Triton, AWS Sagemaker, Kubeflow).
• Excellent demonstrated communication and cross-functional collaboration skills.

Preferred Experience:

• PhD degree.
• Experience working in an FDA-regulated environment.
• Experience with foundation models, e.g. LLMs or Stable Diffusion, Dall-E, etc.
• Experience with optimization, e.g. Bayesian Optimization.
• C++ coding experience.
• Experience with VTK/ITK.
• Experience with Systems Biology models.

Elucid is a hybrid workplace with a strong preference for candidates to live in the greater Boston area. Boston-based employees are strongly encouraged to be in the office on Monday and Wednesday, at a minimum. The office is open 5 days a week for those who prefer to be in person.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Even if you don’t check every box, but see yourself contributing, please apply.

Please click here to apply.