At a Glance
- Tasks: Lead the engineering of machine learning systems from experimentation to production.
- Company: Join a diverse and inclusive tech company focused on innovation.
- Benefits: Enjoy a competitive salary, flexible working options, and career development opportunities.
- Other info: Collaborative culture with a focus on diversity and inclusion.
- Why this job: Shape the future of ML delivery and make a real impact in a data-driven environment.
- Qualifications: Experience in ML systems, cloud platforms, and defining engineering standards.
The predicted salary is between 70000 - 90000 € per year.
Are you ready to define how machine‑learning systems are delivered, operated, and scaled across a data‑driven organisation? As the technical lead within our MLOps function, you will shape how ML is engineered in practice. This role will focus on establishing the standards, patterns, and technical approaches that enable models to move reliably from experimentation into robust production.
You will shape how ML systems are engineered in practice through clear lifecycle standards, reusable approaches, and strong technical foundations.
How you'll contribute- Establish standard, reusable patterns for model serving, pipelines, and deployment.
- Define standards for model packaging, versioning, CI/CD, monitoring and observability.
- Set clear production readiness criteria for models entering engineering workflows.
- Provide technical direction for ML solutions delivered within the team.
- Evolve platform capabilities that reduce bespoke approaches over time.
- Reduce engineering effort required to productionise models by establishing reusable approaches and platform capabilities.
- Strong understanding of serving patterns across batch and real‑time environments, and how models move from training to production.
- You are comfortable operating at the boundary between experimentation and production‑grade ML delivery.
- You value structure, consistency, and high standards in engineering practices.
- You think in terms of reusable frameworks rather than one‑off solutions.
- You are motivated by improving reliability and long‑term maintainability of ML systems.
- You bring clarity, direction, and technical leadership to complex problem spaces.
At NewDay, we value all types of diversity. We’re an equal opportunity employer and believe that our differences create a vibrant, authentic working culture. We want all our colleagues to feel able to bring their whole selves to work. We don’t discriminate on the basis of protected characteristics or identities. We make sure that every job is crafted to be inclusive and that people with disabilities or caring responsibilities can take part in the application and interview process. Tell us if you need accommodations: We’ll put reasonable adjustments in place to support you.
We work with Textio to make our job design and hiring inclusive.
Why this role mattersWe’re looking for these essential skills- Experience building and operating ML systems in production, including model serving, monitoring, and lifecycle management.
- Experience defining engineering approaches that enable Data Science teams to deliver reliable, production‑ready models.
- Ability to turn ambiguity into clear, adoptable technical standards and reusable patterns.
- Experience setting technical direction and influencing engineering practices across teams.
- Hands‑on experience with cloud ML platforms (e.g., AWS SageMaker) and orchestration tools (e.g., Airflow, Step Functions).
Lead ML Engineer employer: NewDay Ltd
At NewDay, we pride ourselves on fostering a dynamic and inclusive work environment where innovation thrives. As a Lead ML Engineer, you will not only shape the future of machine learning within our organisation but also benefit from a culture that values diversity, collaboration, and continuous professional development. With opportunities for growth and a commitment to employee well-being, NewDay is an exceptional place to advance your career in a supportive and forward-thinking setting.
StudySmarter Expert Advice🤫
We think this is how you could land Lead ML 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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that highlight your ability to move models from experimentation to production. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common ML engineering questions and scenarios. Think about how you would establish standards and reusable patterns in real-world situations, as this is key for the role.
✨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.
We think you need these skills to ace Lead ML Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Lead ML Engineer. Highlight your experience with ML systems, model serving, and any relevant cloud platforms. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about ML engineering and how you can contribute to our team. Be sure to mention specific projects or experiences that relate to the job description.
Showcase Your Technical Skills:In your application, don’t shy away from detailing your technical expertise. Mention your experience with CI/CD, monitoring, and observability in ML systems. We love seeing candidates who can clearly articulate their technical journey!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best experience possible. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at NewDay Ltd
✨Know Your ML Fundamentals
Make sure you brush up on your machine learning fundamentals. Understand the lifecycle of ML models, from training to production, and be ready to discuss how you've applied these concepts in real-world scenarios.
✨Showcase Your Technical Leadership
Prepare examples that highlight your experience in setting technical direction and influencing engineering practices. Be ready to explain how you've established standards and reusable patterns in previous roles.
✨Communicate Clearly
Since strong communication is key for this role, practice articulating complex ideas simply. Think about how you can convey your thoughts on model serving and CI/CD processes in a way that's easy to understand.
✨Demonstrate Problem-Solving Skills
Be prepared to tackle hypothetical scenarios during the interview. Show how you would approach ambiguous situations and turn them into clear, adoptable technical standards. This will demonstrate your ability to lead in complex problem spaces.
