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- Tasks: Build cutting-edge AI systems for global retail brands and optimise ML/LLM products.
- 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 making a real impact in the retail industry with AI technology.
- Qualifications: 3+ years in data engineering or MLOps, strong Python skills, and cloud deployment experience.
- Other info: Collaborative environment with excellent career advancement opportunities.
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 is your chance to demonstrate what you can bring to the table beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with Python, MLOps, and cloud platforms like Azure or GCP.
✨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, Python, and any relevant AI libraries. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about working with AI in retail and how you can contribute to our mission. Keep it engaging and personal—let your passion show!
Showcase Relevant Projects: If you've worked on projects involving ML/LLM or backend systems, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions of your work!
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, and cloud platforms like Azure or GCP. Brush up on your experience with ML libraries such as PyTorch and HuggingFace, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built scalable backend systems or developed APIs for AI models. Highlight your role in these projects and any challenges you overcame, as this will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Business Impact
Research how AI is transforming retail analytics and be ready to discuss how your work can contribute to enhancing merchandising and shopper journey planning. Showing that you understand the business side of things will set you apart from other candidates.
✨Be Ready for Collaboration Questions
Since the role involves working closely with data scientists and product teams, prepare examples of how you’ve successfully collaborated in the past. Think about how you can communicate complex technical concepts to non-technical stakeholders, as this is crucial in a cross-functional environment.