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We are a rapidly growing Series-C, Boston-based medical technology company applying machine intelligence to medical imaging to help make more informed decisions on cardiovascular care - leading to better patient outcomes, improved quality of care, and clinicians 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! This is a great opportunity for recent Master's graduates to join a high-performing team, contribute to innovative projects and tackle complex technical challenges.
As a 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, fine-tuning and otherwise harnessing the power of LLMs/LVMs/LMMs, 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.
*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/DL Researchers and 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.
- Expand existing projects and create new projects which leverage large foundation models (LLMs/LVMs/LMMs) against our proprietary data.
- Master’s degree in Machine Learning, computer science, mathematics, statistics or related quantitative field.
- 4+ years overall experience developing ML algorithms.
- 2+ years of prior experience developing ML applications in industry, preferably in the computer vision or biomedical image understanding space.
- Experience with Python and familiarity with Python-based deep learning frameworks (ideally PyTorch).
- Experience with foundation models, e.g. Llama, PaLM, Stable Diffusion, Dall-E, etc.
- Experience with git and an understanding of modern software development methodologies; demonstrated coding ability.
- Basic AWS experience (EC2, S3, etc.).
- Familiarity with modern MLOps tools like Weights & Biases, MLFlow, Neptune, etc.
- Familiarity 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:
- Substantial conference papers, journal publications and/or patents, particularly in the domain of healthcare DL.
- Experience with optimization, e.g. Bayesian Optimization.
- C++ coding experience.
- Experience with VTK/ITK.
- Experience with Systems Biology models.
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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.
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