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For Companies At a Glance
- Tasks: Design and implement cutting-edge ML and AI systems for a revolutionary healthcare platform.
- Company: Join Onsera Health, an innovative 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 advanced technologies.
- Qualifications: 5+ years in machine learning engineering, strong Python skills, and experience with GCP.
- Other info: Ground-floor opportunity to shape the future of population health management.
The predicted salary is between 54000 - 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.
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 in Slough 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 Slough
✨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. We want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission-driven team.
We think you need these skills to ace Senior Machine Learning Engineer in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences that match the Senior Machine Learning Engineer role. Highlight your Python engineering skills, MLOps experience, and any relevant projects you've worked on that align with our mission at Onsera Health.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about healthcare AI and how your background makes you a great fit for our team. Share specific examples of how you've successfully productionised ML models or collaborated across teams in the past.
Showcase Your Projects: If you've got a portfolio of projects or GitHub repositories, don’t hesitate to share them! We love seeing real-world applications of your skills, especially those involving GCP, BigQuery, or Airflow. It gives us a better sense of your hands-on experience.
Apply Through Our Website: We encourage you to apply directly through our website. This way, your application goes straight to us, and we can review it promptly. Plus, it shows you're genuinely interested in joining our mission-driven team!
How to prepare for a job interview at Onsera Health
✨Know Your Stuff
Make sure you brush up on your machine learning concepts, especially those related to productionising models and MLOps. Be ready to discuss your experience with Python, GCP, and any relevant frameworks you've worked with. The more specific examples you can provide, the better!
✨Showcase Your Collaboration Skills
Since this role involves bridging data science and platform engineering, be prepared to talk about how you've successfully collaborated with different teams in the past. Highlight any projects where you translated complex data needs into actionable infrastructure solutions.
✨Prepare for Technical Questions
Expect some deep dives into your technical expertise. Brush up on your knowledge of BigQuery, Airflow, and CI/CD processes for ML workloads. Practise explaining your thought process when tackling challenges, as they might ask you to solve a problem on the spot.
✨Understand the Company’s Mission
Familiarise yourself with Onsera Health's mission and the impact of cardiometabolic conditions. Being able to articulate how your skills can contribute to their goals will show your genuine interest in the role and the company. It’s all about aligning your passion with their vision!
