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 growth opportunities in a dynamic team.
- Why this job: Make a real impact by bridging machine learning research and production.
- 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 Derby 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 environment promotes flexibility while offering competitive compensation, performance bonuses, and share options, ensuring that our employees feel valued and empowered. With a strong focus on employee growth and development, we provide opportunities to lead innovative projects at the forefront of biometric technology, making a meaningful impact in secure digital identity solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Remote ML Infrastructure Lead in Derby
✨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 a CV.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Practice common ML scenarios and be ready to discuss how you've tackled challenges in previous roles. Remember, they want to see how you think and solve problems!
✨Tip Number 4
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 and contributing to our mission.
We think you need these skills to ace Remote ML Infrastructure Lead in Derby
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 passionate about iProov and how your background makes you an ideal candidate for this hybrid leadership role. Be genuine and let your personality come through!
Showcase Your Technical Skills:Don’t hold back on showcasing your technical prowess! Include specific examples of projects where you've designed or improved ML systems, and how you’ve tackled complex engineering challenges. We love seeing real-world applications of your skills!
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 can’t wait to see what you bring to the table!
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, especially around security and diversity. Be ready to discuss how your personal values align with theirs and how you can contribute to fostering an inclusive culture. This will show that you’re not just interested in the job, but also in being part of their community.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about potential challenges in ML infrastructure and how you would address them. Practising these scenarios will help you articulate your thought process clearly during the interview.
