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For Companies At a Glance
- Tasks: Design and implement cutting-edge ML and AI systems for healthcare innovation.
- Company: Onsera Health, a pioneering health AI company transforming cardiometabolic care.
- Benefits: Competitive salary, equity participation, and a dynamic, mission-driven work environment.
- Why this job: Join a world-class team and make a real impact on public health challenges.
- Qualifications: 5+ years in machine learning engineering with strong Python skills.
- Other info: Ground-floor opportunity to shape the future of population health management.
The predicted salary is between 60000 - 84000 £ per year.
The Challenge
Cardiometabolic conditions will impact 80-90% of people throughout their lifetimes, representing the leading cause of death globally and an important risk factor for neurodegenerative diseases and cancer. Sustainably addressing these diseases requires breakthrough therapeutics, AI/ML innovation, and transformative business models that translate clinical outcomes into economic value.
The Opportunity
This is an opportunity to build the ML and AI foundations of Onsera Health's breakthrough healthcare platform. Backed by Population Health Partners (PHP)—the proven venture platform behind Metsera and Corsera Health—we're building the future of population health management.
About the Role
As a Senior Machine Learning Engineer, you will sit at the intersection of data science, platform engineering, and production systems. Your mission is to design and operate the foundations that allow ML, analytics, and agentic AI systems to move safely and reliably from experimentation into regulated healthcare production environments on Google Cloud Platform. You will be the primary interface between Data Science and Platform Engineering, enabling rapid iteration while enforcing production and compliance standards.
Responsibilities
- Design and implement Onsera's agentic AI platform – architect LLM/agent framework selection, standardized patterns for tools, memory, guardrails, evaluation, and observability
- Define MLOps protocols for agentic systems – environment separation, versioning of prompts, tools, and policies, cost controls, rate-limiting, and fail-safe mechanisms
- Bridge data science and platform engineering – translate experimentation needs into GCP infrastructure, scalable compute patterns, and reproducible development environments
- Productionize data science code – convert research-grade notebooks into tested, modular, production-grade Python services, batch and streaming pipelines, and scheduled workflows
- Build production-grade data pipelines – develop idempotent, observable, and cost-efficient pipelines using BigQuery, Airflow, Google Workflows, and Cloud Run
- Implement CI/CD for ML workloads – automated validation, monitoring, rollback strategies, and model lifecycle management
- Establish reliability and governance – logging, metrics, tracing, data quality checks, and auditability for model decisions, data lineage, and agent actions
What We Offer
- Mission-driven work addressing critical public health and healthcare economics challenges
- Ground-floor opportunity to build the ML/AI infrastructure for a breakthrough healthcare platform
- Partnership with a world-class team of industry leaders, innovators, technologists, bioscientists, and clinicians from PHP and beyond
- A fast-paced, dynamic, and highly collaborative work environment
- Competitive salary and benefits package, including participation in our equity program
Minimum Qualifications
- 5+ years of experience in machine learning engineering, data engineering, or a related field
- Strong Python engineering skills with production-quality, typed, and tested code
- Track record productionizing ML models in batch and/or real-time environments
- Hands-on experience with analytical data warehouses (BigQuery or equivalent) and workflow orchestration (Airflow or similar)
- Experience deploying ML systems on GCP, including Cloud Run, GCS, and IAM
- Infrastructure-as-Code experience (Terraform or equivalent)
- Experience with feature engineering, model lifecycle management, and ML evaluation
- Demonstrated ability to collaborate across Data Science, Product, and Platform teams
Preferred Qualifications
- Experience with LLMs, agent frameworks, or AI orchestration systems in production
- Familiarity with prompt management, tool calling, evaluation, and AI safety patterns
- Healthcare or regulated-industry experience, including familiarity with HIPAA or SOC-2 compliance
- Experience with claims data, EHR-derived datasets, or real-world evidence
- Strong written and verbal communication skills with technical and non-technical stakeholders
About Onsera Health
We are an early-stage health AI company revolutionizing cardiometabolic care and population health economics connected to weight loss. Our unique position within the PHP ecosystem provides:
- Venture track record: A proven track record of success in building biotech and healthcare companies
- Deep capital: Funding and resourcing to support deep tech and scientific R&D—and to drive growth
- Strategic guidance: Direct access to industry pioneers (including founders of The Medicines Company and Metsera), healthcare experts (including leaders in virtual care, former FDA commissioners), strategists (McKinsey/QuantumBlack alumni), and world-class scientific talent
- Expert network: Established connections across pharma, payers, and providers
- Startup agility: Ownership in the venture, founder mentality, and ground-floor impact
About PHP
Population Health Partners (PHP) is a premier investment firm established in 2020, aimed at transforming health outcomes for large populations. With offices in New York and London, PHP combines financial resources with industry-leading capabilities and technology. The firm's incubation portfolio includes Metsera and Corsera Health.
Leadership: Led by industry veterans including Clive Meanwell (The Medicines Company), Chris Cox (The Medicines Company), and Whit Bernard (Metsera), bringing decades of founder experience and operational excellence in biopharma and healthcare, and Roy Berggren, 30+ year McKinsey Healthcare leader.
Senior Machine Learning Engineer - Onsera Health in London employer: Jobster
Contact Detail:
Jobster Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - Onsera Health in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those connected to Onsera Health. Use LinkedIn to connect and engage with them. A personal touch can make all the difference!
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in machine learning and AI. Be ready to discuss how your experience aligns with Onsera's mission and the role.
✨Tip Number 3
Showcase your projects! Have a portfolio ready that highlights your best work in ML engineering. This could be anything from GitHub repos to case studies that demonstrate your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Onsera team.
We think you need these skills to ace Senior Machine Learning Engineer - Onsera Health in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior Machine Learning Engineer role. Highlight your experience with Python, ML models, and GCP, as these are key aspects of the job. We want to see how your skills align with our mission at Onsera Health!
Showcase Your Projects: Include specific examples of projects where you've productionised ML models or built data pipelines. This gives us a clear picture of your hands-on experience and how you can contribute to our team. Don't be shy—let your work shine!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use clear language to describe your achievements and skills. We appreciate clarity, and it helps us understand your fit for the role quickly.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy—just follow the prompts!
How to prepare for a job interview at Jobster
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, GCP, and MLOps. Brush up on your experience with BigQuery and Airflow, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly around productionising ML models or building data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
✨Understand the Healthcare Landscape
Familiarise yourself with the healthcare industry, especially regarding compliance standards like HIPAA or SOC-2. Being able to speak knowledgeably about how your work can impact public health will set you apart from other candidates.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in Onsera Health's mission and the role. Inquire about their current projects, team dynamics, or how they envision the future of AI in healthcare. This demonstrates your enthusiasm and engagement.
