At Reach Industries, we believe that scientists are solving some of the world's most pressing challenges, from combating climate change to developing vaccines and new treatments for diseases, yet their tools are still poor. Our AI powered software platform, Lumi, automates operational data capture, insights and processes in labs, augmenting scientists so they can focus on the more creative aspects of their work. Lumi is versatile and is being applied across a wide range of life science industries, including in biotech and pharma.
We are a startup where the early team have a strong background in various frontier technologies and a deep love for making science better. We've already shipped a first version of the Lumi platform and we've received excellent feedback from early customers. We have very ambitious plans for Lumi ahead, so now we're looking for a Lead AI Engineer to become a vital part of our core team, owning the journey of our AI capabilities from research ideas through to robust, production-grade systems that serve the complex needs of our scientific users.
As a Lead AI Engineer at Reach Industries, you will play a crucial role in building and driving the intelligence behind Lumi, from computer vision models that understand what is happening in a lab to LLM-powered features that reason over protocols and scientific workflows. Working with people throughout Engineering and Product, your team will transform unique requirements into AI capabilities that genuinely work in the real world. Being requirements led, you will draw from your existing confidence in applied machine learning and research new models, techniques and tooling in order to output bespoke, best-in-class solutions.
This role involves technical leadership, team mentorship, leading a team of our seasoned AI Engineers, and owning the full lifecycle of our AI work: ideation, applied research, rapid prototyping, productionisation and ongoing operation. You will drive best practices in experimentation, evaluation, MLOps and production engineering, and collaborate closely with stakeholders to deliver impactful projects that advance our mission and deliverables. You will work with cross-functional teams to ensure our models integrate seamlessly with backend and frontend systems while delivering accurate, reliable and performant AI in production. As part of our team, you'll shape a tool that empowers scientists globally, opening new horizons for efficiency and innovation in scientific research.
Your Impact
- Technical Leadership: Lead the design and build of Lumi's AI capabilities, from real-time computer vision pipelines to LLM-driven features, with a strong focus on accuracy, reliability and real-world performance.
- Team Management: Guide, mentor, grow and support a team of AI Engineers, fostering skill growth and ensuring engineering and research best practices.
- Research to Production: Own the journey from ideation to operation: frame problems, direct applied research and prototyping, then harden the winners into tested, monitored, production-grade services.
- Model & Code Quality: Ensure quality through rigorous evaluation frameworks, thorough code reviews, automated testing and adherence to high development standards.
- Performance & AI Operations: Optimise models and inference for accuracy, latency and cost, and own the operational side of AI in production: monitoring, drift detection, versioning and continuous improvement of deployed models.
- Tech Stack Ownership: Stay updated on the rapidly evolving AI landscape (models, frameworks, tooling and research), and make recommendations for continuous improvement. This covers both the product and the development process itself: you will champion AI-assisted engineering tools such as Claude Code and agentic workflows, and set the standard for how your team uses them to move faster without sacrificing quality.
- Cross-Functional Collaboration: Reporting to the Engineering Manager, you will coordinate with Backend Engineers, Frontend Engineers, and Design teams along with the CTO and other Leads to ensure seamless integration and delivery of features. Collaborating with the CEO on any prototyping requirements and wider company initiatives.
- Project Delivery: Lead the successful delivery of projects within deadlines, ensuring alignment with business objectives against roadmaps and deadlines. Delivery leadership means transparency as much as momentum: you surface blockers, risks and things that simply aren't working as early and as loudly as you report wins, solving issues quickly at your level or escalating them without delay, and you keep adapting how the team delivers as engineering practice rapidly changes.
Your Experience
- Minimum of 5-6 years of experience as an AI/ML Engineer with a strong focus on shipping models to production, with at least 2 years experience in a Leadership/Mentoring role.
- Proven track record of taking AI systems from research or prototype through to scalable, reliable production deployment.
- Proficiency in Python, PyTorch (or equivalent), Git, Docker and modern ML tooling.
- Experience in computer vision, such as object detection, tracking, pose estimation or video understanding.
- Experience with MLOps practices: containerised deployment, CI/CD for models, model versioning, monitoring and CPU/GPU infrastructure in the cloud and/or at the edge.
- Experience building with LLMs and foundation models: fine-tuning, retrieval, agentic workflows and structured outputs, with the evaluation discipline to prove they work.
- Strong grounding in data: dataset curation, annotation pipelines, evaluation methodology and metrics design.
- Understanding of real-time inference on streaming data such as live video, and the optimisation techniques it demands (e.g. ONNX, TensorRT, quantisation).
- Knowledge of API design and deploying models as services that integrate with wider backend systems.
- Confidence in software engineering fundamentals: testing, project structure, code quality and disciplined review. You hold strong opinions on what good engineering looks like, loosely held enough to evolve them as agentic workflows rapidly change how software gets built, and you can lead a team through that change without letting standards slip.
- Excellent communication, problem-solving, and decision-making abilities, with a collaborative mindset.
Benefits
- Competitive salary depending on applicant experience and skill level.
- Stock Options We want our team to be a part of our success and offer all permanent team members stock options
- Holiday 27 days + Bank Holidays + Birthday off + Company closure between Christmas and New Year
- BUPA health insurance for you and your family
- Pension Contribution 8% from us and 1% from our employees
- Flexible working with an 8am-10am start and 4-6pm finish
- Enhanced Parental Leave
- Hybrid working, with time in our Bristol HQ when required
Celebrating Diversity
- We encourage, support and celebrate diversity in the workplace and in all aspects of life. We are proud to be an equal opportunity employer who strives to ensure a balanced and measured approach to all aspects of employment.
- We want this to be the best place you've ever worked; a fun environment where you will positively influence the culture and have the freedom and confidence to do your best work with the respect and trust of your colleagues.
Skills Required
- 5-6 years of experience as an AI/ML Engineer, with at least 2 years in a leadership/mentoring role
- Proven track record of taking AI systems from research/prototype to scalable, reliable production deployment
- Proficiency in Python
- Proficiency in PyTorch (or equivalent)
- Experience with Git
- Experience with Docker and containerised deployment
- Experience in computer vision (object detection, tracking, pose estimation, video understanding)
- Experience with MLOps practices: CI/CD for models, model versioning, monitoring, CPU/GPU infrastructure (cloud or edge)
- Experience building with LLMs and foundation models: fine-tuning, retrieval, agentic workflows, structured outputs and evaluation
- Strong grounding in data: dataset curation, annotation pipelines, evaluation methodology and metrics design
- Understanding of real-time inference on streaming data (live video) and optimisation techniques such as ONNX, TensorRT, quantisation
- Knowledge of API design and deploying models as services that integrate with backend systems
- Solid software engineering fundamentals: testing, project structure, code quality and disciplined code review
- Excellent communication, problem-solving, decision-making abilities and collaborative mindset
What We Do
At Reach Industries, We are an early stage start-up with a mission to augment scientists and make labs more efficient, so they can better and faster tackle world challenges. Our intelligent platform, Lumi™, leverages Computer vision, Voice and Machine Learning to capture and analyse operational data. It works as a true assistant across all stages of Life Sciences Development, from Research to Production environments. Lumi™ starts by automating the capture of data associated with experiments, observations and material usage, and can do so much more. Lumi™ saves valuable time, so that scientists can focus on the science and more important matters and increase reproducibility.
