Senior Machine Learning Engineer
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Full-Time 48000 - 72000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Build the ML and AI foundations for a revolutionary healthcare platform.
  • Company: Join Onsera Health, an innovative health AI company transforming population health.
  • Benefits: Competitive salary, equity participation, and a dynamic work environment.
  • Why this job: Make a real impact in healthcare while working with cutting-edge technology.
  • Qualifications: 5+ years in machine learning engineering and strong Python skills required.
  • Other info: Collaborate with industry leaders and enjoy excellent career growth opportunities.

The predicted salary is between 48000 - 72000 ÂŁ per year.

This is an opportunity to build the ML and AI foundations of Onsera Health's breakthrough healthcare platform. The client, backed by Population Health Partners (PHP)—the proven venture platform behind Metsera and Corsera Health, is 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.

Expected compensation for this role: $160,000–$220,000 (base + bonus), plus equity and benefits. Pay varies based on geography and prior experience.

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 employer: Zebra People

Onsera Health is an exceptional employer for those looking to make a meaningful impact in healthcare through cutting-edge AI and machine learning. With a mission-driven culture, competitive salary packages, and the opportunity to collaborate with industry leaders, employees are empowered to innovate and grow within a dynamic and supportive environment. The unique backing of Population Health Partners provides deep resources and strategic guidance, ensuring that team members can thrive while addressing critical public health challenges.
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Contact Detail:

Zebra People 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 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 is your chance to demonstrate what you can do beyond just a CV—make it pop!

✨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 projects in detail. Confidence is key!

✨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

Machine Learning Engineering
Data Engineering
Python Programming
MLOps Protocols
Google Cloud Platform (GCP)
BigQuery
Airflow
Infrastructure-as-Code (Terraform)
Feature Engineering
Model Lifecycle Management
Collaboration Skills
LLMs and Agent Frameworks
Healthcare Compliance (HIPAA, SOC-2)
Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV is tailored to highlight your experience in machine learning engineering and data engineering. Use keywords from the job description to show that you’re a perfect fit for the role.

Showcase Your Projects: Include specific 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.

Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about healthcare AI and how your skills align with our mission. Be genuine and let your personality shine through!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss any important updates from our team.

How to prepare for a job interview at Zebra People

✨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 examples where you've successfully productionised ML models or built 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 healthcare regulations like HIPAA and SOC-2 compliance. Being able to speak knowledgeably about how your work can impact patient care and data security will set you apart from other candidates.

✨Communicate Effectively

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 clearly with both technical and non-technical stakeholders is crucial.

Senior Machine Learning Engineer
Zebra People

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