Strategic Overview
Staff Machine Learning Engineer at Bayesian Health is defined by the responsibilities and candidate requirements in the employer's listing.
The published role emphasizes work such as Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
The role is listed for United States with a remote working arrangement, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
Read more about our recent publication in Nature Medicine that associates our products with lives saved.
Key Responsibilities & Objectives
- Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
- Productionizing: The same models that you develop with production-grade python.
- Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploying production-grade Python code to implement those strategies.
- MLOps: Build infrastructure that enables ML model development and deployment in production systems.
Required Qualifications & Candidate Blueprint
- Ph.D. in a relevant field plus 3+ years relevant experience, or a relevant Master’s degree and 5+ years experience shipping ML based software products.
- Experience owning your ML models from prototyping to production.
- Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems.
- Experience using MLOps tools such as SageMaker and MLFlow.
Preferred Qualifications
- Experience going 0-1 and shipping high impact AI/ML products.
- Experience building solutions within healthcare and/or familiarity working with messy health data.
- Experience working with enterprise customers, and the agility and responsiveness they require.
- Comfortable interpreting / leveraging state-of-the-art peer-reviewed methods or tools in designing your approach.
- Excitement for Bayesian’s mission and being a bar raiser so we can accelerate the pace at which we create value.
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
Staff Machine Learning Engineer
In Brief
We’re an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
Part Data Scientist (building models), part Applied Scientist (productionizing models), and part MLE (deploying, maintaining), also known as “Full Stack Data Scientist” – someone who wants to own the end-to-end effectiveness of their real-time models in a live, clinical AI product.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
Read more about our recent publication in Nature Medicine that associates our products with lives saved.
What You’ll Do
As a Staff Machine Learning Engineer, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you aren’t afraid to get your hands dirty by writing data mapping code, debugging a specific patient case by following patient data as it moves through our AWS services, or improving the timeliness of your model’s predictions by reading and writing production-grade Python and SQL code.
Responsibilities
Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
Productionizing: The same models that you develop with production-grade python.
Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploying production-grade Python code to implement those strategies.
MLOps: Build infrastructure that enables ML model development and deployment in production systems.
Minimum qualifications
Ph.D. in a relevant field plus 3+ years relevant experience, or a relevant Master’s degree and 5+ years experience shipping ML based software products.
Experience owning your ML models from prototyping to production.
Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems.
Experience using MLOps tools such as SageMaker and MLFlow.
Preferred qualifications
Experience going 0-1 and shipping high impact AI/ML products.
Experience building solutions within healthcare and/or familiarity working with messy health data.
Experience working with enterprise customers, and the agility and responsiveness they require.
Comfortable interpreting / leveraging state-of-the-art peer-reviewed methods or tools in designing your approach.
Excitement for Bayesian’s mission and being a bar raiser so we can accelerate the pace at which we create value.
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This opening may suit candidates who can demonstrate experience relevant to the employer's published requirements. Its strongest career signal is the scope of the work itself — particularly Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods. — rather than a generic title alone.
Resume & Application Strategy
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