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- Tasks: Build scalable AI systems for top global retail brands and optimise data pipelines.
- Company: Fast-growing startup redefining retail analytics through innovative AI solutions.
- Benefits: Remote work flexibility, competitive salary, and opportunities for professional growth.
- Why this job: Join a dynamic team and make a real impact in the retail industry with cutting-edge technology.
- Qualifications: 3+ years in data engineering or MLOps, strong Python skills, and cloud deployment experience.
- Other info: Collaborative environment with a focus on innovation and career advancement.
The predicted salary is between 48000 - 72000 £ per year.
Do you want to build agentic AI systems used by over 30 global retail brands?
Looking to scale ML/LLM products in a fast-growing, post-Series A startup?
Keen to work hands-on with MLOps, LLMs, and backend APIs in a high-impact role?
*The role is largely remote, but you must be open to visiting HQ in Bath, UK, 1-2 days a month*
We\’re working with a company that’s redefining retail analytics through AI. Their suite of intelligent tools—used by over 30 global brands—enhances merchandising, shopper journey planning, and range optimisation. Profitable from day one and now scaling fast, they’re growing their engineering team to meet rising client demand. This Senior AI Engineer will work across the business to ideate LLM use cases and own data pipelining, ML deployment and finetuning.
Responsibilities:
- Build scalable backend systems powering ML/LLM-driven tools
- Design and maintain CI/CD-enabled MLOps pipelines
- Develop robust APIs to serve production AI models
- Collaborate with data scientists and product teams
- Optimise big data and cloud infrastructure (Azure/GCP)
Requirements:
- 3+ years in data engineering or MLOps
- Strong Python and exposure to ML/AI libraries (e.g. PyTorch, HuggingFace)
- Proficient with Airflow, DBT, Docker, Kubernetes
- Cloud deployment experience (Azure preferred)
- Backend/API development experience with client-facing exposure
Interested? Please apply below.
Senior AI Engineer - Retail AI employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer - Retail AI
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with AI and retail. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML/LLM. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common coding challenges and be ready to discuss your past experiences with MLOps and backend systems.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior AI Engineer - Retail AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with MLOps, ML/LLM products, and backend APIs. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about building AI systems for retail and how your background makes you the perfect fit. Keep it engaging and personal!
Showcase Your Technical Skills: We’re looking for strong Python skills and experience with tools like Airflow, Docker, and Kubernetes. Be sure to mention specific projects or achievements that demonstrate your expertise in these areas.
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. Don’t miss out!
How to prepare for a job interview at Harnham
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, MLOps tools, and cloud platforms. Brush up on your experience with libraries like PyTorch and HuggingFace, as well as your knowledge of CI/CD pipelines and API development.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially related to data engineering or ML deployment. Think about how you optimised systems or improved processes, and be ready to share those stories during the interview.
✨Understand the Business Impact
Since this role is about building AI systems for retail, it’s crucial to understand how your work can enhance merchandising and shopper journeys. Research the company’s clients and think about how your contributions could directly impact their success.
✨Be Ready to Collaborate
This position involves working closely with data scientists and product teams. Prepare examples of how you’ve successfully collaborated in the past, and be ready to discuss how you would approach teamwork in this new role.
