Machine Learning Engineer

We’re looking for a senior-level Machine Learning Engineer to join a fast-growing health-tech startup working on large-scale data ingestion and normalization using LLMs and modern MLOps tools. This is a hybrid position based in Boston, with flexibility to work remotely and join quarterly in-person team gatherings.

About the Role

As the first Machine Learning Engineer on the team, you’ll lead the design, deployment, and scaling of machine learning systems that process millions of clinical records. You’ll collaborate closely with software and data engineers to build real-world ML products with a clear impact on healthcare data access and usability.

You’ll Be Responsible For:

• Designing and implementing end-to-end ML pipelines with a focus on LLM-based data processing
• Owning model lifecycle: from data prep, training, and evaluation to deployment and monitoring
• Collaborating with backend and data engineers to integrate ML outputs into production systems
• Mentoring engineering teammates on ML best practices, tooling, and system design
• Evaluating new frameworks, models, and tools for continuous improvement

What You Bring:

• 3+ years of experience in machine learning engineering with models in production
• Proficiency in Python and experience with modern ML frameworks (PyTorch, TensorFlow)
• Familiarity with MLOps tooling (MLflow, Airflow, Kubeflow, SageMaker, Vertex AI, etc.)
• Experience working with unstructured data at scale; comfort with AWS or GCP
• Strong communication skills and experience mentoring other engineers

Bonus If You Have:

• Experience with LLMs, transformers, or NLP-driven systems
• Background in healthcare, clinical data, or health-tech
• Familiarity with data quality, observability, and real-time ML systems

Role Type:

• Remote, quarterly in-person company collaboration, networking & team building.
• Competitive compensation package with base, equity, and benefits