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For Companies At a Glance
- Tasks: Design and deliver cutting-edge AI and data systems for next-gen analytics.
- Company: Fast-growing AI startup reimagining brand collaboration with innovative tech.
- Benefits: Up to £80,000 salary, equity, remote work, and career growth opportunities.
- Why this job: Lead impactful AI projects and shape the future of technology.
- Qualifications: Strong AI engineering experience, Python proficiency, and MLOps knowledge required.
- Other info: Join a dynamic team and influence product direction in a lean environment.
The predicted salary is between 48000 - 64000 £ per year.
Senior AI & ML Engineer (Backend / Data Engineering) | Up to £80,000 + Equity | Remote (1 day/month in Bath)
A fast-growing, venture-backed AI startup is seeking a Senior AI & ML Engineer to design and deliver cutting-edge AI and data systems that power its next-generation analytics and visualization products.
This is a hands-on, high-impact role where you’ll own end-to-end projects across machine learning, large language models (LLMs), and data engineering, helping shape the company’s technical direction and building scalable systems from the ground up.
The Company
An innovative technology business reimagining how brands and retailers collaborate, combining machine learning, big data, and immersive visualisation to drive smarter commercial decisions. The team is around 15 people and growing quickly, with AI at the heart of the product suite.
The Role
You’ll take technical ownership of AI and data engineering projects, working across:
- End-to-end ML pipelines – design, build, and deploy production-grade MLOps systems.
- Big data architecture – manage and optimise large-scale data pipelines using tools like Airflow, DBT, and Spark.
- LLM integration – develop and operationalise advanced language models into real-world products.
- Backend development – build scalable, secure, and performant APIs and services to deliver ML capabilities at scale.
- Collaboration – work with data scientists and product teams to take prototypes through to production.
This role suits someone who enjoys full ownership, variety, and solving complex technical challenges in a lean, agile environment.
You’ll Bring
- Strong experience in AI engineering or ML backend development, with a foundation in data engineering and MLOps.
- Expert-level proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow, Hugging Face).
- Practical experience with MLOps principles, including CI/CD for ML, monitoring, and deployment.
- Strong understanding of LLMs, NLP, and modern data infrastructure.
- Familiarity with cloud platforms (AWS, GCP, or Azure), containerisation, and scalable backend architecture.
- Excellent communication skills and a proactive approach suited to startup environments.
Nice to have:
- Experience with streaming data (Kafka, Flink) or data warehousing (Snowflake, Redshift, BigQuery).
- Contributions to open-source or applied AI research projects.
Key Details
- Salary: Up to £80,000 + equity
- Location: Remote, with 1 day/month in Bath
- Start date: By end of 2025 (maximum 1-month notice)
- No visa sponsorship available
Why Join
- Full ownership of end-to-end AI and data projects
- Real-world application of LLMs, ML, and big data in a high-growth setting
- Opportunity to influence architecture and product direction
- Equity and long-term career growth as the company scales
If you’re an AI Engineer or ML Backend Developer ready to lead full-lifecycle AI projects in a fast-growing environment, we’d love to hear from you.
AI Engineer - Data/MLOps employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer - Data/MLOps
✨Tip Number 1
Network like a pro! Reach out to people in the AI and ML space, especially those who work at startups. Use platforms like LinkedIn to connect and engage with them. You never know when a casual chat could lead to a job opportunity!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving MLOps and LLMs. Share it on GitHub or your personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by practising coding challenges and system design questions. Focus on areas like Python, ML frameworks, and big data architecture. The more comfortable you are with these topics, the better you'll perform when it counts!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your experience with AI engineering and MLOps, and let us know how you can contribute to our innovative team.
We think you need these skills to ace AI Engineer - Data/MLOps
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in AI engineering and MLOps. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects and technologies you've worked with!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how you can contribute to our innovative team. We love seeing passion and personality, so let that come through!
Showcase Your Technical Skills: When applying, make sure to mention your proficiency in Python and any ML frameworks you’ve used. We’re particularly interested in your hands-on experience with MLOps principles, so give us the details on your past projects!
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 from our team!
How to prepare for a job interview at Harnham
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and ML frameworks like PyTorch and TensorFlow. Brush up on your understanding of MLOps principles and be ready to discuss how you've applied them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in AI engineering or data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers, highlighting how you tackled complex technical issues and what the outcomes were.
✨Demonstrate Collaboration Experience
Since this role involves working closely with data scientists and product teams, be ready to share examples of successful collaborations. Discuss how you’ve contributed to team projects and how you communicate technical concepts to non-technical stakeholders.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s tech stack, their approach to AI and data projects, and the team dynamics. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.