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 bonus, share options, and great company benefits.
- Other info: Hybrid role with excellent growth opportunities in a dynamic team.
- 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 Peterborough employer: iProov
iProov is an exceptional employer that champions diversity and inclusion, creating a supportive environment where every employee can thrive. With a hybrid work model based in the vibrant WeWork Waterloo, employees benefit from competitive compensation, performance bonuses, and share options, alongside opportunities for professional growth in cutting-edge biometric technology. Join us to be part of a team that values innovation and collaboration, empowering you to make a meaningful impact in the world of secure digital identity.
StudySmarter Expert Advice🤫
We think this is how you could land Remote ML Infrastructure Lead in Peterborough
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues 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 to ML infrastructure. This gives you a chance to demonstrate your hands-on experience and technical prowess beyond just your CV.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Practice explaining complex concepts clearly and concisely, as well as how you’ve collaborated with teams in the past. We want to see how you can bridge the gap between research and production!
✨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 Peterborough
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:Your cover letter is your chance to shine! Use it to tell us why you're excited about the role and how your background makes you a great candidate. Don’t forget to mention your passion for building scalable systems and working in diverse teams.
Showcase Your Projects:If you've worked on relevant projects, make sure to include them! Whether it's a personal project or something from your previous job, we want to see how you've tackled challenges in ML infrastructure and what impact you made.
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. Plus, we love seeing applications come in through our own channels!
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. Brush up on your knowledge of MLOps, CI/CD workflows, and cloud platforms. Being able to discuss specific technologies and how they relate to iProov's needs will show that you're not just a candidate, but a potential leader.
✨Showcase Your Problem-Solving Skills
Prepare to discuss past challenges you've faced in ML infrastructure and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your hands-on experience and strategic thinking, which are crucial for this role.
✨Emphasise Collaboration
iProov values teamwork across various departments. Be ready to share examples of how you've successfully partnered with data scientists, software engineers, and other stakeholders. Highlighting your ability to bridge gaps between teams will resonate well with their culture.
✨Align with Their Values
Familiarise yourself with iProov's commitment to diversity, equality, and inclusion. Be prepared to discuss how you can contribute to fostering an inclusive environment. Showing that you align with their values will set you apart as a candidate who fits into their culture.
