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Bayesian Health

Staff Machine Learning Engineer

Undisclosed

Remote — the employer does not say where candidates may be based.

Location not stated

Employer listed it 21 months ago · Added 4 days ago

Been open since 21 months ago. Long-running listings are sometimes left up after the role is filled.

Salary

Not stated

Location

Location not stated

Timezone

Not stated

Contract

Full-time

Experience

Lead

Category

Data

This employer didn't state pay. Jobs like this usually pay around $185k–$265k a year, a typical range taken from 158 lead-level data roles on Nomaders that do state pay. It's a guide, not an offer.

Remote flexibility

Undisclosed

The listing is advertised as remote but does not state which countries or regions candidates may work from.

Why this role is Undisclosed

We only label a role Work from anywhere, Region restricted or Work from home when the employer's own wording says so. We checked this advert under our current rules and found no country or region eligibility requirement in it. We don't guess, so it stays Undisclosed until the employer publishes enough location information. Here is exactly what the advert left out.

  • Countries you can work from: Not stated. The advert only gives "Remote", which names no country you must live in.
  • Whether the work is remote: Never mentioned. The role reached us through a remote job board, but the advert itself doesn't say the work is remote.
  • Working hours: Not stated. No timezone overlap or set hours are mentioned, so assume nothing either way.

Worth a look all the same. Missing wording is usually a rushed job posting rather than a closed door, so ask where you can be based in your first message, before you write a tailored application.

What the employer says

  • Source listing states candidate location: "Remote"

What Nomaders makes of it

  • No residency or region requirement found in the job description
  • Check with the employer before assuming you can work from abroad

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

About the role

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.

Requirements

  • ·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

Benefits

No benefits package published with this listing. Ask about it at first interview.

How to apply

  1. 1Check the flexibility label above, undisclosed, matches where you plan to live and work.
  2. 2Tailor your CV to the role at Bayesian Health, mentioning your remote working experience.
  3. 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 5d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.

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