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Bask Health

Machine Learning Engineer

Reposted 13 Days Ago
Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.
The summary above was generated by AI

Bask Health is at the forefront of the health-tech industry, providing personalized healthcare experiences through advanced, user-friendly technology. Our platform serves as a launchpad for entrepreneurs, doctors, physicians, and influencers in the DTC telehealth sector.

Engineering at Bask Health is AI-first and builder-led. Work starts in an LLM to clarify intent and constraints, moves into tools like Claude and Cursor to explore and build, is tested with real patients and care teams, and then comes back for systems and polish. AI is a default part of how we work, not a side experiment — because moving fast in healthcare requires every advantage.

We are looking for engineers who take end-to-end ownership, treat AI as a real collaborator, and care deeply about building software that meaningfully improves how healthcare is delivered.

What You'll Do

  • Design, build, and ship high-quality product experiences: Own key surfaces and services end to end, from concept through production. Write elegant, well-tested code that makes complex clinical and operational behavior feel simple and reliable.
  • Work AI-first with Cursor and Claude Code: Use LLMs, Cursor, and Claude Code as your starting point. Draft intent, explore implementations, scaffold components, and refactor with AI in the loop. Apply your own judgment to meet the quality bar healthcare demands.
  • Prototype fast and validate with real users: Build and test implementations quickly with real patients and care teams. Use what you learn to refine before fully committing — especially in sensitive clinical contexts where getting it right matters.
  • Build for scale and own the codebase: Translate product needs into reusable, well-architected patterns. Build in a way that makes the next feature faster to ship and easier to maintain.
  • Make automation legible and trustworthy: Build systems that clearly communicate what AI and automation are doing on behalf of patients and providers. Earn trust through transparency, reliability, and thoughtful defaults.
  • Champion performance, accessibility, and reliability: Ship work that is fast, robust, and accessible. Partner across the team to debug, optimize, and raise the bar over time.
  • Share AI-native workflows: Document prompts, patterns, and workflows that work. Share them across the engineering team so we move faster together without cutting corners that matter to patient outcomes.

Requirements

We are looking for a skilled Machine Learning Engineer to become a key player on our team. The successful candidate will be passionate about crafting sophisticated machine learning models and AI-powered solutions. In this role, you'll tackle a diverse range of projects, and work closely with cross-functional teams to seamlessly integrate AI into our products and services.

Qualifications:

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related STEM field.
  • 3+ years of professional experience in machine learning or computer vision.
  • Strong programming skills in Python and experience with TensorFlow (PyTorch a plus).
  • Hands-on experience building ML pipelines and working with distributed data processing frameworks like Apache Spark, Databricks, or similar.
  • Cloud experience (AWS, Azure, or GCP), including building, deploying, and optimizing solutions with ECS, EKS, or AWS Lambda.
  • Excellent problem-solving skills and ability to work in a collaborative environment.

Benefits

Bask Health is proud to be an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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