Remote Applied Machine Learning Engineer

Description:

• The company is seeking an exceptional product-minded engineer to help scale Vital and meet the market demand for their products across the US.
• They have received investments from renowned investors like Point Nine, 20VC, YC, and angel investors who are founders of successful companies.
• The team consists of AI, ML specialists, and health tech experts who have previously worked at companies like Apple, SpaceX, Ro, Lyft, and Babylon Health.
• The hired engineer will play a crucial role in driving the growth of the product, team, and company as they transition from a startup to a scale-up.
• Responsibilities include writing production-level machine learning models, using cutting-edge ML techniques to predict healthcare diseases, collaborating with the team to build internal tools, and working with domain experts in the health field.
• The tech stack includes Python (Fast API), Go, Typescript, React, React Native, and GCP.

Requirements:

• Proficiency in Python, Go, and Postgres.
• Experience in executing cutting-edge ML techniques to predict healthcare diseases using EMR, Wearables, and Lab testing data.
• Ability to make infrastructural choices to ensure that trained models scale well across large datasets.
• Strong collaboration skills to work with domain experts in the health field and incorporate their knowledge into trained models.
• Experience in running unsupervised anomaly detection on large datasets and making black-box models interpretable.
• Familiarity with training large-scale, weakly-supervised ML models and building dashboards for feedback using human-in-the-loop training techniques.

Benefits:

• Competitive salary ranging from $90k to $200k plus share options for U.S. and Latam employees.
• Opportunity to work remotely on the US East Coast.
• Chance to join a team of experienced AI, ML specialists, and health tech experts who have worked at top companies.
• Involvement in innovative engineering projects and the growth of a startup to a scale-up.
• Ownership of features and the opportunity to be a driving force behind them in the absence of Product Managers.