At a Glance
- Tasks: Design and implement cutting-edge ML and AI systems for healthcare innovation.
- Company: Join 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: Make a real impact on public health while working with industry leaders and innovators.
- Qualifications: 5+ years in machine learning engineering and strong Python skills required.
- Other info: Ground-floor opportunity to shape the future of population health management.
The predicted salary is between 60000 - 84000 ÂŁ per year.
The Challenge
Cardiometabolic conditions will impact *****% 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. 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 ****, 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 in England employer: Onsera Health
Contact Detail:
Onsera Health Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in England
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your past experiences in detail. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining our mission. Plus, it shows you're genuinely interested in being part of our team.
We think you need these skills to ace Senior Machine Learning Engineer in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with Python, GCP, and any relevant ML projects you've worked on. We want to see how your skills align with our mission!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI/ML and how you can contribute to Onsera Health's goals. Be sure to mention any experience in healthcare or regulated industries, as it’s a big plus for us.
Showcase Your Projects: Include links to your GitHub or any projects that demonstrate your ability to productionise ML models. We love seeing practical examples of your work, especially if they relate to the responsibilities listed in the job description.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Onsera Health
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, GCP, and MLOps protocols. 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 productionising ML models or building data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your problem-solving abilities.
✨Understand the Healthcare Landscape
Familiarise yourself with the healthcare industry, particularly around cardiometabolic conditions and compliance standards like HIPAA. This knowledge will help you connect your technical skills to the mission of Onsera Health during the interview.
✨Communicate Clearly with All Stakeholders
Practice explaining complex technical concepts in simple terms. You’ll need to bridge the gap between data science and platform engineering, so being able to communicate effectively with both technical and non-technical stakeholders is key.