Remote ML Infrastructure Lead in York

ML Infrastructure Lead

Role : Senior ML Infrastructure Lead focused on building and scaling the technical foundations for production ML at i Proov.

Hybrid role across ML infrastructure, platform engineering and MLOps.

Reports to : Chief Scientific Officer

Compensation : Negotiable (Base) + 20% Company Performance Bonus + Share Options + i Proov Benefits

We are looking for a highly capable and hands-on leader to design, implement and scale the systems, tooling, processes and standards that enable ML teams to train, deploy, monitor and improve models reliably, securely and at scale.

The role sits at the intersection of machine learning, software engineering, data, cloud infrastructure and platform reliability, bridging research and production.

It suits someone who can think strategically about long-term platform capability while remaining technically hands-on to solve complex engineering and operational challenges.

Impact : Lead the design and evolution of our ML platform, infrastructure and MLOps; build and maintain scalable, reliable, and secure systems for model training, testing, deployment, monitoring and lifecycle management; develop tooling to enable ML Engineers, Data Scientists and Researchers to work efficiently and ship models with confidence; define robust CI/CD workflows, model versioning, reproducibility, experimentation, feature management and release management; own and improve production ML environments with strong standards for availability, performance, observability and resilience; monitor model and platform health, data quality, drift, latency, throughput and cost efficiency; build self-service tooling to reduce friction for ML teams; partner with ML, Data, Software and Platform Engineering to productionise models and improve the end-to-end lifecycle; support scaling for training and inference workloads including high-throughput or compute-intensive use cases; drive governance, security, compliance, auditability and operational rigor across the ML lifecycle; improve efficiency and cost-effectiveness of ML systems; mentor engineers and act as a technical leader; help define the roadmap for ML enablement.

What we would like to see from you

You will have experience in high-growth, fast-paced tech environments and are passionate about building and launching quality products with positive impact.

You are an experienced product leader with a background in security (IAM) or enterprise Saa S, combining strategic vision with operational rigor to deliver usable, secure, and elegant technical solutions.

• Proven experience in a senior MLOps, ML Platform, ML Infrastructure, Platform Engineering or Machine Learning Systems role
• Strong hands-on background in software engineering and cloud infrastructure, with direct experience supporting production ML environments
• Experience building and operating systems that support the full ML lifecycle (experimentation, training, deployment, monitoring)
• Strong knowledge of Python and engineering practices (testing, automation, code quality)
• Strong experience with cloud platforms such as GCP
• Experience with Docker, Kubernetes and modern containerised deployment patterns
• Strong experience with CI/CD, infrastructure-as-code and workflow orchestration
• Experience with tools like Airflow or similar platforms
• Understanding of model observability, data quality, feature pipelines, lineage and reproducibility
• Experience designing scalable infrastructure for ML workloads (training, batch inference and real-time serving)
• Commitment to reliability, security, governance and operational excellence in production systems
• Ability to operate across both strategic and hands-on technical work
• Strong communication skills and ability to collaborate across engineering, product and data teams
• Nice-to-haves
• Experience supporting computer vision, deep learning, LLM or compute-intensive ML workloads
• Experience with GPU infrastructure, distributed training or HPC environments
• Familiarity with feature stores, model registries and automated retraining pipelines
• Experience building internal developer platforms or self-service ML tooling
• Experience in regulated, high-security or high-availability environments
• Experience leading or mentoring engineers in scale-up/high-growth contexts
• Familiarity with responsible AI, model governance or risk controls in production ML

Benefits

• 25 days annual leave plus 8 bank holidays; additional days based on continuous service
• Growth shares after probation (6 months)
• Salary sacrifice schemes including Pension, Cycle To Work and Electric Car
• Nursery Sacrifice Scheme
• Work Overseas perk – opportunity to work globally for up to 2 weeks
• Life Assurance
• Smart Health – private GP, psychologist, nutritionist and tailored fitness plans for you and your family
• 1:1 career coaching with in-house Occupational Psychologist
• Award-winning L&D platform with personal training budgets
• Enhanced paid family leave
• Pension: 5% employee, 3% employer
• Flexible hybrid working environment
• Barista coffee/tea, snacks in the We Work office
• We Work discounts and online well-being sessions
• Vitality Health options including private health cover and gym membership discounts

The Vitality Programme includes additional rewards for all employees, such as private health benefits, gym discounts, wellness perks and exclusive partner offers.

Our Culture & Recruitment Process i Proov emphasizes curiosity, collaboration and psychological safety.

We are an equal opportunities employer and welcome applicants from all backgrounds.

Our recruitment process focuses on qualifications, competence and fit for the role.

If you need an adjustment for any reason during hiring, please contact our team at careers@iproov. com.

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