AI Engineer

Materiom

Materiom is seeking a full-time, hands-on Research Scientist to support our in-house experimental data generation efforts, developing protocols on automated platforms, and performing experiments and characterizations on bio-based material systems and natural polymers. The goal is generating the high-quality experimental data that drives our AI/ML-accelerated discovery and modelling platform for sustainable polymeric materials.  * Location: London, UK * Role Type: Full-time, on-site * Salary Range: £40K-55K About Materiom Materiom is an impact-focused, non-profit tech startup with the mission to accelerate the research, development, and uptake of bio-based materials that have a net-positive impact on the planet. We do this by building datasets and software tools for scientists, producers, and brands. The Materiom Commons is our open platform, providing a large open database of material formulations and AI features to support a community of 20,000+ scientists, designers, engineers and entrepreneurs to quickly and easily find bio-based solutions for packaging and textiles applications. We are developing our next-generation innovation platform through  investments in data mining, predictive models and in-house experimental data generation. Our interdisciplinary team blends deep expertise in circular economy, materials science, AI, and software development, and provides opportunities to learn from a diversity of perspectives. We’re creative optimists driven by a belief in collective action. About the Role This is a hands-on role for someone who thrives in a wet lab, particularly working with testing various polymer formulations and the properties of materials made using these formulations at different processing conditions. The role sits at the intersection of formulation science, polymer and material characterisation, and data-driven experimental design. You will develop protocols for experimental testing with automated liquid-handling platforms, generate clean, structured, high-quality experimental datasets that feed directly into our machine learning workflows, and help shape the feedback loop between physical experiments and predictive models. Key Responsibilities * Plan and run lab-scale formulation experiments on liquid-based biopolymer systems including dispersions and solutions * Characterise liquid formulations using methods such as rheology as well as spectroscopic techniques including FTIR and UV/Vis * Prepare material samples and characterize their physical and chemical properties * Operate and develop methods on automated liquid-handling and high-throughput platforms to increase experimental throughput * Design and perform structured experiments to explore formulation and process variables efficiently and maximise the information gained from each run * Generate clean and well-structured datasets, ensuring data quality and integrity for downstream analysis and modelling * Analyse and interpret experimental results to identify trends and structure–property relationships, using these insights to guide subsequent experiments * Work within machine learning, active learning and agentic AI workflows, translating model-guided recommendations into experiments and feeding results back into the loop * Maintain rigorous lab records, follow good laboratory and chemical-safety practice, create and document protocols for reproducibility * Collaborate with internal scientists, engineers and with external partners to improve and diversify the generated experimental data * Maintain, calibrate and troubleshoot laboratory instruments to keep experimental workflows running reliably Required Qualifications * PhD or MSc in Materials Science, Polymer Science, Chemistry, Chemical Engineering or a related field * Hands-on laboratory experience working with polymers (ideally bio-based / natural), with a demonstrated ability to plan and run experiments and characterisations independently * Practical experience preparing and testing end materials in various forms * Working knowledge of Design of Experiments (DoE) and a structured, data-driven approach to experimentation * A genuinely hands-on, bench-oriented mindset, with strong lab discipline and attention to data quality * Excellent communication skills and the ability to thrive in an interdisciplinary team  Preferred Qualifications * Industry experience (corporate or startup) working with polymers, ideally bio-based or natural ones * Experience with automated liquid-handling / high-throughput experimentation platforms or self-driving / autonomous labs, including basic familiarity with computer programming to review and debug orchestration scripts * Exposure to active learning or other data-driven / machine learning approaches to materials and formulation optimisation  * Experience scaling formulations and materials from lab to pilot or manufacturing scale  What We Offer Materiom is an impact-focused startup offering a supportive and flexible environment where you can drive the acceleration of net-positive materials using cutting-edge technology. Our benefits include * Competitive Salary: An annual salary range of £40K-55K, commensurate with your experience and expertise. * Annual Bonuses: Eligibility for performance-based bonuses to reward your contributions to the company’s success. * Generous Paid Time Off: 30 days of paid holiday per year for full-time positions, in addition to all UK bank holidays. * Learning & Mentorship Grants: An annual individual budget dedicated to developing your hard and soft skills. * Commuter Support: Access to a Bike2Work scheme to support sustainable travel. * International Retreats: Regular company retreats, often held in international locations, to build connection and celebrate progress. * Collaborative Team Culture: Our culture is defined by deep, interdisciplinary collaboration, offering you the exciting opportunity to work at the intersection of materials science and AI to drive positive impact for people and the planet.

Umain AB

At Umain, we're not just creating software; we're crafting the future, one innovative project at a time. With our motto "Shape, Ship, Scale," we empower our team to not only envision the future but also play a pivotal role in building it. We're a dynamic team where you can shape the future, ship groundbreaking solutions, and scale your abilities in many different ways. We're on the lookout for developers ready to join us in this journey, bringing passion, creativity, and dedication along with them. The role is ideal for engineers with demonstrable skills in AI as well as for software engineers who have recently transitioned to AI and ML expertise, and offers an opportunity to develop your craft whilst working closely with clients on delivering AI solutions to real-world challenges. We are seeking an AI Engineer with experience in building robust, scaleable, AI powered solutions. The ideal candidate combines a product engineering mindset with a deep enthusiasm for advancing AI capabilities. They demonstrate a great understanding of core AI concepts, product development workflows, and embodies team spirit. As an AI Engineer at Umain, your role will involve: Assisting our clients in clarifying their questions and determining if using AI is a suitable solution for them You understand the limitations of a model and how to address them within the product's UX Experience architecting agentic solutions (context, memory, and tool/skill handling) and implementing them using frameworks such as Mastra, Microsoft Agent Framework, LangChain/LangGraph. Applying stochastic test casing and trace-based reasoning to evaluate, test, and improve agent behaviour, supported by observability tooling (Langfuse, Promptfoo, etc.). Understanding and applying core AI concepts such as redlining, document chunking for accuracy, efficient use of embeddings, and debugging AI systems Validating, deploying, monitoring, and maintaining built models, ensuring they can be used at scale Developing and maintaining end-to-end data pipelines and machine learning workflows, optimizing for performance and reliability Working with diverse, cross-functional teams on projects that deliver groundbreaking AI solutions for global brands We also welcome experienced software engineers looking to transition into AI: Strong product development background with several years of software engineering experience Active engagement in AI (agents, wrappers, context engineering) Knows how to work efficiently in a product/engineering team Who You Are: We value candidates who demonstrate: Great delivery skills: Proven capability to deliver AI solutions Strong AI intuition: A deep understanding of AI concepts Curiosity: Enthusiasm for emerging technologies, creativity in problem-solving, and an eagerness to learn in a rapidly evolving AI landscape Full-stack product thinking: Frontend or backend experience outside the traditional AI field, with the ability to build end-to-end You're a developer with a passion for innovation and a knack for problem-solving. You're eager to learn, grow, and take on new challenges. You value collaboration, diversity, and the opportunity to make a significant impact. You believe in the power of technology to shape the future. What We Offer: A chance to work closely with global brands on a range of diverse and unique projects that explore and truly push the boundaries of what's possible. A fun and fair work environment where you have the opportunity to expand your skills through unique challenges and fantastic colleagues. A personal coach, and a setting where you can grow professionally and personally. Being part of multidisciplinary teams, participating in agile teams, being an important player in a highly ambitious setting. Why Umain? Career Framework: We believe in fairness and clarity, which is why we've established a transparent career framework to ensure equal pay and equal opportunities for all. Your growth and success are as important to us as they are to you. Together with your coach, you will build your own development plan and grow in your career. Work-Life Balance: At Umain, diversity is our strength. We understand that life doesn't pause when you walk into the office. That's why we've cultivated an environment that supports an excellent work-life balance. We welcome team members from all walks of life, recognizing the richness that different backgrounds, ages, and life stages bring to our team. We're committed to supporting each other, encouraging a healthy work-life balance that respects your needs, whether it's taking care of your family, your pets, or yourself. Innovations and Learning: Technology is always evolving, bringing new challenges and opportunities for collaboration and learning. Our developers work closely with designers, analysts, testers and more to tackle these challenges head-on, sharing knowledge and growing together. Skills Over Degrees: We're more interested in what you can do than in the diplomas you hold. Talent, drive, and creativity are what count at Umain. Here, you'll find opportunities to grow, learn, and excel in your career, regardless of your educational background. If you have the ambition and commitment to succeed, we have the environment and resources to support your journey. Background Check: Umain conducts a background check for final candidates in accordance with our internal policies. The check is carried out only with your consent and is ordered by our CISO through our approved screening partner. The scope of the check depends on the role level. This step is performed late in the recruitment process and is used solely to support a secure and fact-based hiring decision.

Adaptyv Bio

Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE We already use AI across every part of the company — business operations automation, data analysis and reporting, AI-driven review of customer experiment data, agentic workflows for lab scheduling and customer communication, and a lab-wide assistant the team leans on. The capabilities largely exist. What's missing is someone whose entire job is taking what we've already built and making it successful: wrapped, installable, wired into the tools people use every day, and turned into the default way the company works. This is an internal-facing role focused on process optimization. You won't spend most of your time inventing new features — you'll take the capabilities that already exist across LabOS, our internal APIs, and our AI systems and make them genuinely easy to access, reliable, and adopted. The win condition is the rest of the company moving faster because the thing you built became the obvious option. In a given week, that might mean: * Wrapping our internal APIs (lab orchestration, instrument automation, experiment data) into clean, installable SDKs and MCP servers so agents and teammates can plug into them in minutes instead of reverse-engineering endpoints * Building and improving our lab-wide assistant — its system prompt, its skills, and the integrations that let it actually act through our APIs rather than just talk about it * Turning manual business processes into agents and workflows: procurement alerts, invoice reconciliation, revenue and reporting pipelines, customer update drafting * Pulling together experiment, commercial, and operational data to answer questions and surface insights the team would otherwise miss — the analysis nobody has time to do by hand * Taking a powerful-but-buried capability and making it the new default — packaging it, documenting it, putting it where people already work, and making sure it actually gets used * Setting up evals, observability, and monitoring so the systems you build and the models you use perform as expected and catch regressions automatically This is not an ML research role. You won't be training protein language models or publishing papers. You'll be building the applied AI systems, internal tooling, and glue that make a small, fast-moving team operate like one ten times its size. WHAT WE'RE LOOKING FOR * Strong software engineering fundamentals. You build production systems, not notebooks. TypeScript or Python at minimum — but ideally language doesn't matter to you, and you're comfortable in both. * Deep hands-on experience with LLMs and agentic patterns — knowing when and how to apply function calling, tool use, multi-step workflows, MCP, and retrieval to create value. You've shipped real systems, not wrappers around chat completions. * A platform instinct. You like taking something that works for one person and turning it into something the whole team can install and use — good defaults, clean interfaces, and docs that mean nobody has to ask you how it works. * Process-to-agent instinct. You look at a manual business process and immediately see where an agent or workflow would do it better. Then you build it, test it, and hand it over by Friday. * Fluent with data. You can dive into a messy database or spreadsheet, pull the right numbers, and turn them into an answer, a dashboard, or an automated report. SQL and a notebook/BI habit are second nature. * Comfortable working across every team. You'll talk to lab scientists about data review, to ops about procurement, to the commercial team about customer workflows. The AI touches everything. * Ships fast, owns the result. You prototype in a day, get feedback, iterate. And you're responsible for everything your agents produce — shipping fast does not mean dumping slop on the rest of the team. Your systems are maintainable and you can strike the right tradeoff between moving fast now and moving fast in the future. * Curious about biology. No background required, but you should find it genuinely interesting that we're building infrastructure for AI to run experiments in the physical world. Application deadline We are reviewing applicants on a rolling basis.