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 work environment.
- Other info: Collaborate with industry leaders in a fast-paced, supportive atmosphere.
- Why this job: Join a mission-driven team tackling critical public health challenges with innovative technology.
- Qualifications: 5+ years in machine learning engineering and strong Python skills required.
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. 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 research.
Senior Machine Learning Engineer employer: Onsera Health
Contact Detail:
Onsera Health Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those that align with healthcare. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨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
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, ML models, and GCP. We want to see how your skills align with our mission at Onsera Health!
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 transforming healthcare. Let us know why you're excited about this opportunity and what makes you a great fit.
Showcase Your Projects: Include links to any relevant projects or GitHub repositories that demonstrate your expertise in ML engineering and data pipelines. We love seeing practical examples of your work and how you've tackled real-world challenges.
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 the role. We can’t wait to see what you bring to the table!
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 MLOps and productionising models. Be ready to discuss your past experiences with Python, GCP, and any relevant frameworks you've worked with. This is your chance to show off your technical skills!
✨Showcase Your Projects
Prepare to talk about specific projects where you've successfully implemented ML solutions. Highlight the challenges you faced, how you overcame them, and the impact your work had. Use metrics to back up your claims—numbers speak volumes!
✨Understand the Company’s Mission
Familiarise yourself with Onsera Health's goals and the healthcare landscape they operate in. Being able to articulate how your skills can contribute to their mission of revolutionising cardiometabolic care will set you apart from other candidates.
✨Ask Smart Questions
Prepare insightful questions that demonstrate your interest in the role and the company. Inquire about their current ML projects, team dynamics, or how they approach compliance in healthcare. This shows you're not just interested in the job, but also in being part of their journey.