At a Glance
- Tasks: Lead the design and evolution of ML infrastructure and MLOps capabilities.
- Company: Join iProov, a leader in biometric identity assurance with a diverse and inclusive culture.
- Benefits: Negotiable salary, performance bonuses, share options, and great company benefits.
- Other info: Hybrid role with excellent opportunities for career growth and mentorship.
- Why this job: Make a real impact by bridging research and production in machine learning.
- Qualifications: Experience in fast-paced tech environments and strong technical leadership skills.
About iProov
iProov provides science-based biometric solutions that enable the world’s most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award-winning liveness technology and iSOC offer unmatched resilience against deepfakes and generative AI threats while ensuring effortless, scalable user experiences. Trusted by leading governments and enterprises, including the U.S. Department of Homeland Security, U.K. Home Office, GovTech Singapore, ING, and UBS, iProov sets the standard in biometric identity assurance.
This global trust is built not only on our technology but on the strength of the people behind it. For us, diversity at iProov is about reflecting the customers we serve, holding the principles of equality and inclusion at the heart of everything we do and all that we stand for, embracing differences, creating possibilities, and growing together. We aim to foster a culture where individuals of all backgrounds feel confident in bringing their whole selves to work, feel included, and their talents are nurtured, empowering them to contribute fully to our purpose.
The Role
- Reports to: Chief Scientific Officer
- Location: WeWork Waterloo - Hybrid
- Comp: Negotiable (Base) + Company Performance Bonus (20%) + Share Options + iProov Benefits
We are looking for a highly capable and hands-on Senior ML Infrastructure Lead to build and scale the technical foundations that enable machine learning to operate effectively in production. This is a hybrid leadership role sitting across machine learning infrastructure, platform engineering and MLOps. You will be responsible for designing and evolving the systems, tooling, processes and standards that allow ML teams to train, deploy, monitor and improve models reliably, securely and at scale. You will work at the intersection of machine learning, software engineering, data, cloud infrastructure and platform reliability, helping bridge the gap between research and production. This role is ideal for someone who can think strategically about long-term platform capability, while still being technically hands-on enough to solve complex engineering and operational challenges.
How you can make an impact
- Lead the design and evolution of our ML platform, infrastructure and MLOps capability
- Build and maintain scalable, reliable and secure systems for model training, testing, deployment, monitoring and lifecycle management
- Develop the infrastructure and tooling that enable ML Engineers, Data Scientists and Researchers to work efficiently and ship models with confidence
- Design robust workflows for CI/CD, model versioning, reproducibility, experimentation, feature management and release management
- Own and improve the production environment for machine learning systems, ensuring strong standards for availability, performance, observability and resilience
- Define and implement monitoring across model and platform layers, including system health, data quality, drift, latency, throughput and cost efficiency
- Build or optimise internal self-service tooling and platform capabilities to reduce friction for teams working on ML use cases
- Partner closely with ML, Data, Software and Platform Engineering teams to productionise models and improve the end-to-end ML development lifecycle
- Support the scaling of infrastructure for both training and inference workloads, including high-throughput, real-time or compute-intensive use cases where relevant
- Drive best practice in governance, security, compliance, auditability and operational rigour across the ML lifecycle
- Improve the efficiency and cost-effectiveness of ML systems, including cloud resource usage, compute environments and deployment patterns
- Mentor engineers and act as a technical leader across ML platform and operations topics
- Help define the roadmap for ML enablement, ensuring the platform can support current needs while scaling for future growth
What we would like to see from you
You will have experience working in high growth, fast paced tech-first environments. You are passionate about building.
Remote ML Infrastructure Lead in Milton Keynes employer: iProov
iProov is an exceptional employer that champions diversity and inclusion, fostering a culture where every individual can thrive and contribute their unique talents. Located in the vibrant WeWork Waterloo, our hybrid work model offers flexibility while providing access to a collaborative environment that encourages innovation and growth. With competitive compensation packages, including performance bonuses and share options, we empower our employees to make a meaningful impact in the field of biometric identity assurance.
StudySmarter Expert Advice🤫
We think this is how you could land Remote ML Infrastructure Lead in Milton Keynes
✨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 or GitHub repository showcasing your projects and contributions. This is a great way to demonstrate your expertise in ML infrastructure and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to ML infrastructure. Practice explaining your thought process and problem-solving approach, as this will help you stand out during discussions.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at iProov.
We think you need these skills to ace Remote ML Infrastructure Lead in Milton Keynes
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the ML Infrastructure Lead role. Highlight your hands-on experience in machine learning, platform engineering, and MLOps to show us you’re the perfect fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about this role at iProov. Share specific examples of how you've tackled challenges in ML infrastructure and how you can contribute to our mission of secure biometric solutions.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Mention the tools, languages, and frameworks you’ve worked with, especially those relevant to ML systems, cloud infrastructure, and CI/CD processes.
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 out on any important updates from our team!
How to prepare for a job interview at iProov
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest machine learning infrastructure trends and tools. Familiarise yourself with MLOps practices, CI/CD workflows, and cloud platforms that are relevant to the role. Being able to discuss specific technologies and how they can be applied at iProov will show your technical prowess.
✨Showcase Your Leadership Skills
As a Senior ML Infrastructure Lead, you’ll need to demonstrate your ability to lead teams and projects. Prepare examples of past experiences where you’ve successfully guided a team through complex challenges or implemented new processes. Highlight your mentoring skills and how you’ve helped others grow in their roles.
✨Understand iProov’s Mission
Dive deep into iProov’s mission and values. Understand their focus on security, diversity, and user experience. Be ready to discuss how your personal values align with theirs and how you can contribute to fostering an inclusive culture while driving technical excellence.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving abilities. Think about potential challenges in ML infrastructure and how you would address them. Practising these scenarios will help you articulate your thought process clearly and demonstrate your strategic thinking.
