About Hey Savi Hey Savi is a fashion tech startup here to spark a new era in fashion discovery, igniting body confidence in everybody and every body. Think Shazam meets Spotify, but for fashion. As a female-founded startup, we’re at an exciting stage and shaping something truly game-changing in the world of fashion discovery.

Our community doesn’t want to scroll through paid ads and dead-end links. They want fashion that fits – in stock, in their size and at the best price – with a search experience that puts them at the centre. We’re creating a movement, not just a product, and we're looking for someone brilliant to help lead the charge.

The Role: Lead Data Scientist, Computer Vision

We’re seeking an exceptional Lead Data Scientist to architect, build, and productionise the computer vision intelligence engine at the core of Hey Savi.

This pivotal role requires you to personally design, implement, deploy, and iterate on state-of-the-art computer vision models, from image processing and embedding, to object detection and advanced agentic AI systems.

You will function as a technical principal, driving the long-term data and AI strategy and making high-stakes, pragmatic trade-offs on technical direction alongside the founders, product and engineering teams.

This role is for a highly experienced engineer who demands 90% hands-on technical contribution and genuine ownership of the production system, not for a pure people manager or a research-focused position.

Requirements What You'll Be Responsible For

Hands-on Computer Vision Leadership

• Personally design, build and deploy production computer vision and agentic AI systems that power search, discovery, recommendations and personalisation.
• Own the full data science lifecycle: problem framing, data exploration, modelling, evaluation, deployment, monitoring and iteration of production systems.
• Make pragmatic trade-offs between speed, quality and technical elegance in an early-stage environment.

Product & User Impact

• Translate messy user problems into clear, testable interventions.
• Partner with Product to ensure models improve user trust, confidence and discovery - not just offline metrics.
• Laser focus on feature value, return on investment, and optimising for the right signals

Data Reality & Foundations

• Work hands-on with imperfect datasets.
• Design annotation strategies, data quality checks and evaluation frameworks from scratch.
• Decide where data investment matters - and where it doesn’t (yet).

Technical Direction & MLOps

• Establish pragmatic MLOps practices: deployment, monitoring, alerting and iteration.
• Work closely with Engineering to build scalable but lightweight data and ML pipelines (AWS).
• Ensure models are robust, reliable, scalable, explainable where needed and safe to operate in production.

Team & Culture (Now and Future)

• Set a strong technical and ethical bar for data science at Hey Savi.
• Mentor and guide future data scientists as the team grows.
• Model curiosity, humility and ownership in a high-ambiguity startup environment.

Must-haves

• Bachelor or Master in Computer Science, Mathematics, or a related field with a focus on Machine Learning or Data Science.
• Strong expertise in Computer Vision and hands-on experience with fine-tuning state of the art models.
• Deep learning expertise and domain knowledge (e.g. PyTorch, CUDA, model optimisation for training/inference in a commercial setting).
• Strong MLOps and engineering mindset, including CI/CD, automated deployment, and model monitoring.
• Strong understanding of data engineering, data quality, and annotation strategies.
• Comfortable operating in fast-paced environments and adapting direction as priorities evolve

Nice-to-haves

• Track record of deploying production AI/ML systems at scale (supporting 100K+ users or processing high-volume workloads)
• Experience building and leading teams and working effectively with senior stakeholders.
• Experience in fashion, e-commerce, search, recommendations or consumer-facing products.
• Experience building and maintaining agentic AI production systems and LLMOps
• Experience designing ML systems with limited data and budget.

What Success Looks Like (6–12 Months)

• Core Computer Vision systems live, improving and trusted.
• Clear signal on what drives real user value.
• AI tooling and practices embedded internally, not ad hoc.
• Strong partnership between Data Science, Engineering, Product and founders.
• A foundation that can scale - without premature complexity.

Benefits What You’ll Get

• A leadership role shaping a movement-led fashion-tech brand
• A creative, fast-paced, values-led environment that champions individuality
• Hybrid working – up to 2 days IRL with the team in London, 3 days remote
• £85-110k salary based on experience
• Equity stake

We strongly encourage people of all backgrounds, identities, body types and lived experiences to apply. We’re building a brand that celebrates individuality – and our team should reflect that too.