Our Job Openings
Staff Machine Learning Engineer - Bayesian Health
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.
Head of Data Science & Machine Learning - AQMed
Company Overview
SandboxAQ is a high-growth company delivering AI solutions that address some of the world’s greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world’s epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
About the Role
Join AQMed to revolutionize heart health using AI and advanced sensing for next-gen medical diagnostics. You will lead our Data Science/ Machine Learning (DS/ML) team and deliver impactful data products to benefit patients and physicians worldwide. In close collaboration with Product and Engineering, you will be responsible for designing and building data products that provide actionable and useful insights that are derived from our proprietary hardware & data. You excel in user-centricity, project execution, and you drive the development and delivery of data products that solve real-world user problems. You are excited by shipping functional, useful, and market-driven products and iterating them in the real world. The success indicators for this role include product adoption, user satisfaction, regulatory & quality success, time-to-market, and business impact.
What You’ll Do
- As one of the AQMed leads, you’ll work closely with Product & Engineering to define the vision, strategy, and roadmap for data products that align with business objectives, incorporating ML capabilities where valuable. Curiosity & partnership are critical: you will be working alongside other leads to optimize the entire signal processing chain, from sensors to final data output.
- Collaborate with AQMed leads to periodically and relentlessly prioritize our work to achieve BU-level goals using an OKR framework.
- Exemplify user-centricity by working closely with our clinical partners. Through rapid prototyping and iterative development, turn clinical insights, user needs, and business goals into clear product requirements and design specifications. Prioritize features by balancing business impact, user feedback, and technical feasibility to drive meaningful outcomes.
- Establish & track progress of DS/ML team-level OKRs, oversee timelines and budgets, and drive the end-to-end lifecycle of data products to ensure successful delivery and impact. Ensure the scalability, usability, and impact of ML models in production environments.
- Skillfully balance the need to execute quickly with the need to uphold a high standard in research. Keep abreast of the cutting-edge techniques that align with product requirements.
- Be a confident representative of AQMed internally within SandboxAQ and externally (for example, with clinicians, development partners, regulators, industry partners, etc). Identify opportunities (e.g. conference presentations & proceedings, peer-reviewed journals) to elevate our team members & showcase our team’s capabilities.
- Lead & mentor a multidisciplinary team of data scientists and ML engineers. Foster a collaborative and innovative work environment, driving professional growth and excellence.
About You
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10+ years in engineering and product leadership roles: You have served as an individual contributor in an engineering role. You have been an engineering manager. You excel as a leader at the intersection of Product Development & AI/ML.
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Advanced degree in engineering, computer science, AI, mathematics, or a related field Strong experience in AI-enabled data/software medical product development from concept development (stage 0-3) through commercialization (stage 4+)
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You effectively communicate at the executive level, ensuring decisions are clearly linked to business objectives and routed to appropriate stakeholders for efficient action.
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Action-oriented: you proactively create solutions, knowing that a delay in our product launch means a delay in impacting patient care.
Nice to Haves
- Cardiovascular device/cardiology experience and familiarity/expertise in the electrophysiology of the heart.
- You are willing and able to work from our Palo Alto location 50% of the time (hybrid).
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