Research engineer

Research Engineer

Bigblue

📍 Paris | Full-time | Fluent 🇫🇷 & 🇬🇧   At Bigblue, we're building the logistics backbone for the next generation of commerce. Modern brands sell everywhere: through their own online stores, marketplaces, retail, social commerce, and more. Across every channel, customers expect the same fast, reliable, and transparent experience after they buy. What used to be Amazon's exclusive advantage is now becoming the standard for every ambitious brand. We're helping them get there. Since 2018, we've built a tech-driven fulfilment platform used by 600+ brands, including Muji, Aigle, Scuffers, and Cabaïa. With 200+ Bigbluers across the UK, France, Spain, and Germany, our proprietary tech stack, and a network of 9 warehouses and over 100,000 sqm of fulfilment space across Europe, we ship millions of orders every month. And we're nowhere near done! Backed by €20M+ in funding, we're expanding across Europe and building the operating system that will power modern commerce operations at a global scale. At Bigblue, we hold ourselves to a very high bar: in the quality of our product, the rigour of our operations, and the care we bring to every merchant we work with. You'll be working alongside talented people on real, high-impact problems, in an environment where high standards come with genuine support, ownership, and room to grow. If you want your work to matter from day one, you're in the right place.     The Role   As an Applied Scientist, you will develop and maintain efficient and robust algorithms that significantly improve our warehouse operations. You'll work at the intersection of research and engineering, identifying optimization opportunities, collaborating with stakeholders on operational feasibility, and shipping solutions that have immediate, visible impact on our European fulfillment network.   This is probably one of the highest-leverage job openings we have today – each percentage of performance we squeeze out of our algorithms allow us to scale even faster.   What You Will Work On Identify optimization opportunities across our WMS algorithms Align with stakeholders on operational feasibility and discuss tradeoffs Develop and maintain efficient and robust algorithms that significantly improve our operations Collect feedback, measure performance and iterate based on real-world results

Research Engineer

Kog

About Kog Kog builds the fastest LLM inference engine on standard datacenter GPUs. Our Kog Inference Engine generates 3,000 output tokens per second per request on a single 8× AMD MI300X node and 2,100 on an 8× NVIDIA H200 node (FP16, batch size 1, no speculative decoding). We co-design the model architecture and the execution engine together. Our Laneformer model uses Delayed Tensor Parallelism (DTP), a novel architecture that restructures the Transformer dependency graph so inter-GPU communication overlaps with computation rather than blocking it. We pre-trained a 2B-parameter DTP model on 6T tokens on 256 H100 GPUs. We are a team of 11 people, including 10 engineers and 5 PhDs. Test it at playground.kog.ai. Read the technical details on the Kog Labs blog. What you will work on You will imagine, design, and run experiments to understand how architectural decisions propagate through inference behavior, morph existing open-weight models into architecture variants optimized for speed, and turn findings into measurable gains in generation speed and model quality. * Design new model architecture variants, including routing strategies, attention mechanisms, and MoE structure, with execution constraints as a first-order design input. * Extend the Laneformer thesis by exploring inference-aware architectural variants such as DTP, Ladder Residual, and PT-Transformer, and finding what compounds at scale. * Own the post-training pipeline across fine-tuning, evaluation methodology, and adaptation of existing open-weight models toward architecture variants optimized for inference speed. * Scale the stack to large MoE models such as DeepSeek v4 and Qwen 3, working through routing, expert parallelism, and communication patterns at inference time. * Write up findings as research papers, submit them to top venues, and present them at conferences. * Contribute to building AI agents that will perform architecture research and training experiments autonomously, starting from the research foundations we are building now. What we look for * You have designed or changed model architecture, where the structure itself was the object of the work. Showing that work, a paper, a repository, or a thesis, is a requirement to move forward. * You reason about model design and hardware together, tracing how communication structure and layer dependencies shape inference behavior, with fluency in Transformers and MoE deep enough to weigh trade-offs. * Stronger signals include inference-aware architectural variants such as DTP, Ladder Residual, or PT-Transformer, and post-training methods such as fine-tuning, preference optimization, or quantization, including at research scale. * A top engineering school or a PhD with concrete architecture work counts, even without industry experience. What we offer * Direct access to AMD and NVIDIA datacenter GPUs from day one * A team where creativity and technical judgment carry weight and where the people closest to the problem shape the key decisions * Problems that sit on the critical path of model execution speed and that directly influence what the system can become * A remote-friendly working model, with one mandatory week per month in our Paris office. Travel and accommodation covered by the company. * Compensation aligned with top AI research profiles, including equity

Research Engineer

Relation Therapeutics

ABOUT RELATION Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. THE OPPORTUNITY Join our machine learning group as a Research Engineer and help drive the development, deployment, and scaling of ML and computational systems across the company. You’ll work at the intersection of research and engineering—improving research workflows, supporting rapid experimentation, and enabling teams to push the limits of modern ML. You’ll collaborate with machine learning scientists, data scientists, platform engineers, and other domain experts across the organisation. Depending on priorities, you may work within a specific ML team or operate in a cross-functional capacity. Based at our wet/dry lab and headquarters in central London, you’ll tackle challenges involving large datasets, complex models, and high-performance compute. Your work will strengthen our training and inference pipelines, improve our software foundations, and optimise our hybrid on-prem/cloud environment, which includes dedicated DGX clusters and collaboration with partners like NVIDIA. This role offers a chance to shape the systems and tools that power cutting-edge ML research. DAY TO DAY, YOU WILL * Work with interdisciplinary teams to solve challenges across data engineering, ML engineering, and software engineering. * Build and improve data processing, transformation, and loading systems to support model training and inference at scale. * Develop and maintain high-quality research and production codebases to enable rapid, reproducible experimentation. * Advance our software engineering practices by optimising systems, streamlining pipelines, and improving robustness across workflows. PROFESSIONALLY, YOU WILL HAVE * BSc/MSc/PhD in CS/ML/Engineering (or related), 2+ years industry experience. * Solid understanding of algorithms, data structures, complexity. * Proficiency in Python with clean, maintainable coding practices. * Familiarity with PyTorch and common scientific Python libraries. * Solid understanding of ML fundamentals and modern deep learning. * Experience training, evaluating, and iterating on models. * Familiarity with AWS/GCP, Docker, Kubernetes, and CI/CD. * Familiarity with orchestration tools (Airflow/Prefect) and model-serving frameworks. Bonus experience * Exposure to biology/bioinformatics or ML for scientific domains. PERSONALLY, YOU * Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams. * Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work. * Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect. * Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams. * Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes. WORKING STYLE & CULTURE AT RELATION At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! RECRUITMENT AGENCIES Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. Relation is a committed equal opportunities employer.