Nathan Wills

Machine Learning EngineerLocation: Zurich / RemoteLanguage: German/Swiss German Preferred (English Fluent/Professional) This is a priority search for a small investment group building an internal AI Lab across companies they actively own.The company operates across retail and FMCG supply chains. Their portfolio supports large offline and online retailers, with heavy operational workflows across trading, pricing, ERP, and CRM. Today a lot of value is lost to manual processes and fragmented systems.This hire will be the first dedicated technical builder in the AI Lab. The focus is hands on delivery, not research.The expectation is to design, build, and ship AI driven systems that improve trader productivity, reduce operational friction, and surface revenue opportunities. This includes agent based workflows, internal tools, and hands on AI and ML implementation.You would work closely with founders and operators, move quickly, and have real autonomy. There is also exposure to reviewing the technical architecture of new investments and shaping build decisions early.Small, elite team distributed across Europe. High responsibility and clear ownership from day one. Real upside tied to equity backed projects.Ideally Switzerland based. German or Swiss German is a strong plus, English is also required.If you enjoy building in ambiguous environments and want your work in production immediately, feel free to send your CV.

Lead AI Engineer Fully Remote - Europe I am working with a European health tech scale up that is building production grade AI systems used by insurers, governments, hospitals, and pharma groups to support complex drug pricing and reimbursement decisions.They are hiring a Lead AI Engineer to own the AI architecture end to end and drive how LLM based systems are designed, evaluated, and shipped into production.The role is hands on and strategic. You would lead AI initiatives across RAG pipelines, agent workflows, and tool orchestration, while mentoring a small engineering team and working closely with product and platform leads. A big focus is on building systems that are observable, cost aware, and reliable, not demos.The environment suits someone who has spent time taking LLM systems from concept to real usage, has strong Python and backend experience, and understands tradeoffs around latency, throughput, and evaluation. Experience with LangChain or LangGraph, FastAPI style services, cloud infrastructure, and MLOps practices is important.The product domain sits at the intersection of healthcare, pricing, and access to medicines, with real world impact and complex constraints. The team is senior, international, and remote first across Europe.If this sounds aligned with the kind of problems you enjoy working on, feel free to share your updated resume/cv!

ML Scientist in AI Explainability  Location: Boston Massachusetts Type: Full time Machine Learning Scientist, AI Explainability and Scientific Discovery We are working with a publicly listed deep tech company operating at the intersection of machine learning, material science, and next generation battery technology. The team is applying AI directly to scientific discovery, with real world impact across energy storage, transportation, robotics, and aerospace. This role sits within an advanced AI research group focused on Large Language Models, AI agents, and explainability in scientific problem solving. Your work will directly influence how new battery materials are discovered and validated using AI. The position can be fully remote. What you will work on You will lead research into machine learning methods for scientific discovery, with a strong focus on multimodal Large Language Models and agent based systems.You will study how LLMs reason, plan, and generate solutions when applied to core scientific and engineering questions, particularly in battery and material design.You will design and optimize training pipelines for large models, tackling challenges around data quality, architecture, scalability, and compute efficiency.You will integrate domain specific data sources such as scientific literature and internal research documents into model training and inference.Your research will be deployed into a production multi agent AI system used for real battery technology discovery.You will collaborate closely with researchers, engineers, and external academic labs, and contribute to publications and conference presentations. What we are looking for An MSc or PhD in Computer Science, Statistics, Computational Neuroscience, Cognitive Science, or a related field, or equivalent industry experience.Strong grounding in machine learning, deep learning, and Large Language Models, with hands on research experience.Solid Python skills and experience with frameworks such as PyTorch or TensorFlow.Experience working with causal graphs and explainability focused AI methods.A proven research track record, ideally including peer reviewed publications.The ability to explain complex technical ideas clearly to both technical and non technical stakeholders.Nice to have Exposure to AI applied to material science, chemistry, or battery systems.Familiarity with recent research methods in LLM optimization and reinforcement learning approaches such as GRPO. What is on offerA highly competitive salary and benefits package, including equity in a publicly listed company.The chance to work on AI for science problems with visible global impact.A collaborative research environment alongside experienced ML scientists, engineers, and domain experts.Strong support for professional development, publishing, and long term career growth.