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For Companies At a Glance
- Tasks: Lead impactful machine learning projects and shape AI strategies.
- Company: Forward-thinking tech company focused on data-driven products.
- Benefits: Fully remote work, flexible hours, and clear career progression.
- Why this job: Make a real impact in AI while mentoring engineers and influencing strategy.
- Qualifications: Strong Python skills and experience with ML frameworks like TensorFlow or PyTorch.
- Other info: Collaborative environment with exposure to diverse ML applications.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Looking for a role that gives you the opportunity to lead impactful machine learning projects while shaping the technical direction of a growing AI function? Excited by influencing strategy, mentoring engineers, and working fully remotely across Europe within a flexible, supportive environment?
THE COMPANY
This organisation is a forward‑thinking technology business building data‑driven products powered by advanced machine learning. They solve complex challenges across areas such as NLP, automation, and large‑scale model deployment. With a distributed technical team across Europe, they emphasise collaboration, experimentation, and strong engineering standards. You will join at a time of investment in AI, where your decisions directly shape the road‑map and overall model capability.
THE ROLE
As a Staff Machine Learning Engineer you will:
- Lead the design, development, and deployment of end‑to‑end ML solutions.
- Architect scalable ML systems and pipelines that integrate seamlessly with cloud infrastructure.
- Mentor engineers, championing best practices across coding, experimentation, and MLOps.
- Collaborate with Product and Engineering teams to define priorities and model strategy.
- Apply deep learning, NLP or classical ML techniques to real‑world, high‑impact problems.
- Uphold responsible AI principles across model development and evaluation.
YOUR SKILLS & EXPERIENCE
The successful Staff Machine Learning Engineer will have:
- Strong Python skills and experience with ML frameworks such as TensorFlow or PyTorch.
- Deep knowledge of machine learning and modern deep learning techniques.
- Experience deploying ML models to production using cloud platforms (AWS, GCP or Azure).
- Familiarity with big‑data or distributed tools (Spark, Kafka or similar).
- A track record of leading complex ML projects and influencing technical decisions.
- Excellent communication skills across distributed, cross‑functional teams.
WHAT THEY OFFER
The successful Staff Machine Learning Engineer will receive:
- Fully remote work across Europe with flexible collaboration hours.
- Modern tooling, supportive leadership, and clear progression into senior technical influence.
- Exposure to diverse ML applications and the chance to shape long‑term AI strategy.
HOW TO APPLY
Please register your interest by applying via the link on this page with your CV.
Staff Machine Learning Engineer in Manchester employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Machine Learning Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend virtual meetups, and connect with potential colleagues 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 machine learning projects, especially those that highlight your experience with Python, TensorFlow, or PyTorch. This will give you an edge and demonstrate your hands-on expertise.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex ML concepts in simple terms, as communication is key when collaborating with cross-functional teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our innovative team and contributing to exciting AI projects.
We think you need these skills to ace Staff Machine Learning Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff Machine Learning Engineer role. Highlight your Python expertise, ML frameworks, and any relevant projects you've led. We want to see how you can contribute to our exciting AI journey!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your experience fits with our mission. Don’t forget to mention your excitement for remote work and collaboration across Europe – we love that vibe!
Showcase Your Projects: If you've worked on impactful ML projects, make sure to include them in your application. Describe your role, the challenges you faced, and the outcomes. We’re keen to see how you’ve influenced technical decisions and led teams in the past!
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 the role. Plus, it shows you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Harnham
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around deep learning, NLP, and the frameworks like TensorFlow or PyTorch. Be ready to discuss specific projects you've worked on and how you tackled complex challenges.
✨Showcase Your Leadership Skills
Since this role involves mentoring and leading projects, prepare examples of how you've influenced technical decisions in the past. Think about times when you’ve championed best practices or guided a team through a tough project.
✨Understand Their Tech Stack
Familiarise yourself with the cloud platforms they use (AWS, GCP, Azure) and any big-data tools like Spark or Kafka. Being able to speak confidently about how you’ve deployed ML models in production will set you apart.
✨Communicate Clearly
As you'll be working with distributed teams, practice articulating your thoughts clearly and concisely. Prepare to discuss how you collaborate with cross-functional teams and ensure everyone is on the same page.
