At a Glance
- Tasks: Lead the development of machine learning capabilities and deliver scalable AI solutions.
- Company: Professional services firm with a growing data and AI team.
- Benefits: Up to £95k salary, bonus, remote work, and potential for permanent role.
- Other info: High-impact role with clear career progression and mentoring opportunities.
- Why this job: Shape the future of ML engineering and work on cutting-edge AI projects.
- Qualifications: Strong ML engineering experience, expertise in Python, and cloud environments.
The predicted salary is between 95000 - 95000 € per year.
A professional services firm is looking for a Lead Machine Learning Engineer to join its growing data and AI team. This is a key role focused on building and leading ML engineering capability, delivering scalable AI solutions, and shaping the organisation’s data and AI strategy.
The role:
- Lead the development of machine learning engineering capability across the business
- Design, build, and productionise ML models and data products
- Develop and implement MLOps frameworks (CI/CD, model deployment, monitoring, governance)
- Build scalable data and ML pipelines on Azure-based platforms
- Collaborate with data scientists, analysts, and stakeholders to deliver end-to-end AI solutions
- Contribute to data architecture, standards, and best practice across the organisation
- Provide technical leadership, mentoring, and guidance to engineers and wider teams
What they’re looking for:
- Strong experience in ML engineering, MLOps, and data/AI architecture
- Proven track record delivering end-to-end ML solutions in cloud environments (Azure preferred)
- Expertise in Python, Spark/PySpark, and modern data platforms (e.g. Databricks)
- Hands-on experience with NLP and LLMs, including deployment and optimisation
- Experience building scalable pipelines, model governance processes, and production systems
- Ability to translate business requirements into robust technical solutions
- Strong stakeholder management and leadership experience
Why apply:
- Opportunity to build and shape ML engineering within a growing data function
- High-impact role with ownership of architecture, tooling, and best practice
- Exposure to modern AI and LLM use cases
- Clear pathway to a permanent role
Please note: sponsorship is not available for this role.
Lead Machine Learning Engineer 12m FTC in Nottingham employer: Harnham
Join a forward-thinking professional services firm that prioritises innovation and employee development, offering a dynamic work culture where your contributions directly shape the future of machine learning engineering. With a focus on collaboration and mentorship, you'll have the opportunity to lead impactful projects while enjoying a flexible remote work environment and a competitive salary package. This role not only provides a clear pathway to permanent employment but also positions you at the forefront of cutting-edge AI solutions in a supportive and growth-oriented setting.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer 12m FTC in Nottingham
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. The more people you know, the better your chances of landing that Lead Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving Azure and MLOps. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with Python, Spark, and building scalable pipelines. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications.
We think you need these skills to ace Lead Machine Learning Engineer 12m FTC in Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Lead Machine Learning Engineer role. Highlight your expertise in ML engineering, MLOps, and any relevant projects you've worked on, especially those involving Azure.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led ML projects or collaborated with teams to deliver AI solutions. Show us your passion for data and AI!
Showcase Your Technical Skills:Don’t forget to mention your hands-on experience with Python, Spark/PySpark, and any modern data platforms like Databricks. We want to see how you’ve applied these skills in real-world scenarios, especially in cloud environments.
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’re considered for this exciting opportunity to shape ML engineering at StudySmarter!
How to prepare for a job interview at Harnham
✨Know Your ML Stuff
Make sure you brush up on your machine learning engineering knowledge. Be ready to discuss your experience with MLOps, Python, and Azure. Prepare examples of how you've built and deployed ML models in the past, as this will show your practical expertise.
✨Showcase Your Leadership Skills
Since this role involves technical leadership, think about times when you've mentored others or led a project. Be prepared to share specific examples that highlight your ability to guide teams and manage stakeholders effectively.
✨Understand Their Needs
Research the company’s data and AI strategy. Understand their current challenges and think about how your skills can help them achieve their goals. This will not only impress them but also allow you to tailor your answers to their specific needs.
✨Prepare for Technical Questions
Expect some technical questions related to building scalable data pipelines and model governance. Practice explaining complex concepts in simple terms, as this will demonstrate your ability to communicate effectively with both technical and non-technical stakeholders.
