Staff Machine Learning Engineer
At a glance
Senior Machine Learning Engineering role at Bayesian Health, Inc. Remote, United States · full-time · no salary stated · we estimate $181,150–$247,500 across the United States.
Bayesian Health, Inc. has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and refine machine learning models and labelers around clinical use cases and current research methods
- Move the models you create into production, then improve deployed systems with production Python code
- Trace patient data through AWS services to investigate individual cases and fix data mapping issues
- Develop Python and SQL code to make model predictions more timely and assess their performance
- Create infrastructure that supports model development and deployment in live systems
What you bring
- A relevant Ph.D. plus at least three years of related work, or a relevant master’s and five years shipping ML software
- You have taken machine learning models from early prototypes through production use
- You write production Python and SQL to implement and evaluate models in live systems
- You have used MLOps platforms such as SageMaker and MLFlow
Who this fits
This staff-level role suits an engineer who wants responsibility for models from experimentation through their performance in a live clinical product. The position is remote within the United States.
From the employer
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.
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.