--- title: 'Machine Learning Engineer – Lumen Enterprise Models (SWE-focused LLMs) at Cosine' canonical: 'https://feeny.ai/job/machine-learning-engineer-lumen-enterprise-models-swe-focused-llms-cosine-london-7hvn96cw2cfb' type: 'job' last_seen: '2026-10-19' --- # Machine Learning Engineer – Lumen Enterprise Models (SWE-focused LLMs) at Cosine - **Company:** Cosine - **Location:** London, United Kingdom - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-10-15 - **Last confirmed live:** 2026-10-19 - **Apply:** https://jobs.ashbyhq.com/cosine/d8578852-be21-4435-a837-19d3dd447893 ## Job description Job title: Machine Learning Engineer – Lumen Enterprise Models (SWE-focused LLMs) Location: London; full in-office working as default Start date: ASAP Reports to: CEO Compensation: Salary and Equity options available for discussion Application deadline: 08/11/26 at 23:59 UK time ___________________________________________________________________________ Help train the software engineers of the future Cosine is building autonomous software-engineering systems for organisations where reliability, security and control matter most. Our Lumen Enterprise models are designed to work across real codebases. They need to understand unfamiliar architectures, make changes across multiple files, use tools, run tests and produce software that engineers can maintain and trust. We’re looking for a Machine Learning Engineer to help train and improve these models. You’ll work across the full training stack, including pre-training, supervised fine-tuning and reinforcement learning. This is a truly unique role that will provide exposure across all areas of the model training lifecycle. WE’re looking for someone who is just as happy to profile the training loop, identifying performance bottlenecks and memory leaks, as implementing new RL algorithms. This is a hands-on role for someone who enjoys working close to the model and cares about the quality of the software it produces. ___________________________________________________________________________ ## The role You’ll work closely with research, infrastructure and product to answer questions such as: - What should Lumen learn next? - Which data and environments will teach it most effectively? - How should we reward correct, maintainable and useful software? - How do we train models to work across large repositories and long contexts? - How do we know when a model is genuinely better for engineers? The models you train will write code, use development tools, run tests and receive feedback from real software-engineering environments. Your work will directly influence how Lumen reasons about code, navigates unfamiliar systems and improves through experience. ___________________________________________________________________________ ## Why this role matters The best coding models are not simply the ones that generate plausible code. They need to understand context, respect existing architecture, use tools effectively, test their work and recover when their first attempt fails. They need to produce changes that work in the real world, not just on a benchmark. That behaviour has to be trained. You’ll work directly on the data, environments, rewards and evaluations that shape Lumen’s capabilities. Your work will influence the models used by engineers and enterprise teams working on complex and security-sensitive software systems. This is an opportunity to work on frontier model training while staying close to a concrete, high-value outcome: building AI that can genuinely do software engineering. ___________________________________________________________________________ ## What you’ll do - Work across the full training lifecycle, running pre-training, supervised fine-tuning and reinforcement-learning experiments. - Optimize training methods at scale on frontier models. - Diagnose and fix performance bottlenecks and communication overhead in distributed training environments. - Train models on long-context, multi-file and repository-level tasks. - Develop RL and RLVR loops using signals from execution, tests, linters, static analysis and other engineering feedback, turning fresh ideas into scalable, reproducible code. - Investigate model failure modes such as poor planning, brittle fixes, reward hacking and regressions. - Collaborate with infrastructure, platform and data teams. ___________________________________________________________________________ ## What we’re looking for You may come from machine learning research, applied ML, model training or a closely related engineering background. You should have: - Strong experience training deep-learning models in a production or research environment. - Deep practical experience with PyTorch or a comparable framework. - Experience with distributed training and multi-GPU systems (FSDP, Deepspeed, …) - Strong software-engineering fundamentals and a high bar for correctness and maintainability. - Clear communication and the ability to explain technical trade-offs. - Experience with large language models is important. You should have worked meaningfully on at least one of, pre-training, SFT, preference optimisation, RLHF or RLVR. We care more about depth of understanding and evidence of strong technical judgement than about having used every tool listed. Even if you don’t tick every box, please consider applying! A bonus if you have - Experience with mixture-of-experts (MoE) architectures. - Experience with CUDA. - Familiarity with vLLM, SGLang or other high-performance inference systems. - Experience running jobs on SLURM, Kubernetes or managed GPU platforms. - Experience with code-model benchmarks such as SWE-bench, HumanEval or internal repository-level evaluations. - Contributions to open-source model-training, RL or evaluation tools. ___________________________________________________________________________ ## Why join Cosine - Direct impact: Your work directly shapes the next generations of Lumen Enterprise SWE models that engineers use every day. - Real scale: You’ll work with large, modern open-source models, long context lengths, and multi-node training runs. - Full-stack ML engineering: From custom PyTorch code and distributed systems to data curation, RL design and MLOps. - Research + pragmatism: You’ll stay close to the latest literature in SFT, and code LLMs, but you’ll be judged by shipped improvements, not just ideas. If this sounds like a fit, this is a role where you can meaningfully push the frontier of open-source–based software engineering models. ___________________________________________________________________________ Cosine is an equal opportunity employer. We value diverse backgrounds, perspectives, and ways of thinking, and we’re committed to creating an inclusive and respectful workplace. We encourage applications from anyone who meets the role requirements, even if you don’t meet every single qualification. If you need reasonable adjustments at any stage of the hiring process, we’re happy to discuss them. ___________________________________________________________________________ ## Compensation, Benefits & Ways of Working We’re an in-office team, five days a week, by design. We believe the work we’re doing benefits from being together, collaborating closely, and building shared context. What you can expect: - Competitive salary, benchmarked to the market - Equity / share options, so you share in the upside you help create - 30 days’ holiday + bank holidays - Work hard in the office, collaborate closely, and switch off properly - Dog-friendly office — bring your dog to work - Weekly team breakfast & lunch - Monthly socials - Pension - High-quality equipment to do your best work We care about focus, sustainability, and doing great work — not performative overwork. We value people who show up, contribute thoughtfully, collaborate well with their colleagues, and then go home. This role won’t suit everyone. But if you’re looking for a fast-moving environment, close collaboration, and a team that takes both the work and work-life balance seriously, it’s a great place to be. ___________________________________________________________________________ Agency & Data Protection Notice To comply with UK GDPR and our internal data-protection and equal-opportunity obligations, we only accept candidate applications and agency submissions via our Applicant Tracking System (ATS). This ensures appropriate privacy notices, lawful processing, auditability, and consistent retention controls. Any CVs or candidate details received outside the ATS (including via email, Slack, or direct message) will be treated as unsolicited, will not be considered as part of the recruitment process, and will not give rise to any fee or payment obligation. ## About Cosine ## Company Overview - **One-liner**: Cosine is a sovereign AI frontier lab and developer of Lumen, a specialist coding model and fully agentic software engineering system that outperforms generalist models on real-world code tasks. - **Entity Type**: Private (Venture-backed) - **Headquarters**: London, United Kingdom - **Founded**: 2022 - **Founders**: Yang Li, Alistair Pullen, Sam Stenner ## Core Business - **Primary Industry**: Artificial Intelligence, Software Development - **Target Customers**: Enterprise, Defense, Finance, Government, Healthcare, and other high-security, high-trust environments (B2B) - **Mission**: Build sovereign AI engineering systems that serious teams can rely on in secure environments where reliability, privacy, and control matter most. ## Products & Services - **Lumen (Model Family)**: A specialist family of AI models trained exclusively on production-quality code. Outperforms generalist models (OpenAI, Anthropic, DeepSeek) on code benchmarks. Includes variants: - **Scout** (8B parameters): Fast, on-device, for in-repo context. - **Outpost**: Post-trained from Kimi K2.6, optimized for enterprise and niche languages (COBOL, Fortran, Verilog, Rust, complex SQL). - **Frontier**: Highest-performing model (coming soon), achieving 59.3% on internal Niche-Bench vs. GPT-5.4 (47.4%). - **Cosine Agent**: A fully agentic SWE that allows users to work on tickets asynchronously. Operates within a terminal-native interface, with multi-agent orchestration, MCP tool access, and a local-to-remote execution model. - **Cosine Cloud**: Fully managed public cloud offering for teams. - **Enterprise Deployment**: Managed single-tenant cloud and fully air-gapped on-premise deployments for maximum security. ## Market Standing - **Valuation**: Not disclosed - **Key Metric**: Annual Revenue of **$1.0M** (as of latest data); Total Funding of **$3.0M**. - **Funding History**: - Pre-Seed (Nov 2022): $500K, led by Y Combinator (W23 batch). - Seed (Aug 2024): $2.5M, led by UpHonest Capital and Soma Capital (6 investors). - Grant (Apr 2026): 1 investor. - **Notable Investors/Partners**: Y Combinator, UpHonest Capital, Soma Capital; Member of UK government’s £500M **Sovereign AI programme**; granted access to the **Isambard-AI** supercomputer. - **Growth Signals**: Headcount has grown **60.9% YoY** (to ~23 employees); has assembled a UK Sovereign AI coalition of defense, infrastructure, financial, and healthcare leaders. Models have topped public benchmarks for two consecutive years. ## Competitive Advantages - **Specialist-Over-Generalist Moat**: Lumen is a model trained exclusively on production code, not general text; this leads to significantly better results on code benchmarks (e.g., 59.3% on Niche-Bench vs. GPT-5.4’s 47.4%). - **Sovereign AI**: First company to train, own, and deploy a fully sovereign AI model entirely on UK soil. This is a critical differentiator for defense, national security, and critical infrastructure where foreign AI is legally off the table. - **Full-Stack In-House Build**: Owns the entire stack (models, agent infrastructure, evaluation, product surfaces, deployment) allowing deep integration and rapid iteration. - **Real-World Deployment**: Deployed in air-gapped, on-premise environments for security-conscious customers who cannot use cloud-based AI. ## Strategic Focus - **Sovereign AI Leadership**: Deepening its role as Britain’s national AI champion, working with the UK government on the £500M Sovereign AI programme. - **Enterprise & Government Sales**: Expanding into defense, finance, infrastructure, and healthcare with secure, private deployments. - **Pushing Agentic Boundaries**: Moving beyond chat and autocomplete to build AI agents that plan, reason, write, test, and ship code inside real development workflows. - **Technical Scaling**: Building larger, more capable Frontier models and improving the training infrastructure (synthetic data, RL, reward functions). ## Why Work Here - **Pioneering Work**: Build the future of autonomous software engineering at a company that leads the field in code-focused AI. - **High Ownership**: Engineers own the full stack; work directly influences what the product becomes. - **Culture**: Emphasizes direct communication, deep ownership, customer obsession, and “doing the hard thing.” Avoids performative overwork (standard 9-5, no regular late work or weekends). - **In-Office by Design**: Primarily in-office (London) for close collaboration and fast feedback. - **Benefits**: Competitive salaries, share options, pension (NEST), cycle-to-work scheme, weekly free meals, unlimited snacks/drinks, pet-friendly office, monthly team breakfasts/socials, quarterly offsites. Can request to work abroad up to one month per year. - **Team**: Small (~23 people), high-agency, with deep technical talent. - **Open Roles** (as of latest): ML Systems Engineer (Model Training & Infra), Full Stack Product Engineer, Strategy & Operations. ## Sources 1. [cosine.sh](https://cosine.sh/) 2. [cosine.sh/careers](https://cosine.sh/careers) 3. [Y Combinator](https://www.ycombinator.com/companies/cosine) 4. [LinkedIn](https://uk.linkedin.com/company/cosine-ai) 5. [Ashby Jobs](https://jobs.ashbyhq.com/cosine) ## Other roles at Cosine - [Applied ML Technical Lead, Defence](https://feeny.ai/job/applied-ml-technical-lead-defence-cosine-london-5c1qhcd3naj2) — London, United Kingdom - [Defence Account Director](https://feeny.ai/job/defence-account-director-cosine-london-6tdgd3k097py) — London, United Kingdom - [Founding Healthcare Lead](https://feeny.ai/job/founding-healthcare-lead-cosine-london-q1j3kqfat5s0) — London, United Kingdom - [Strategic Partnerships Manager](https://feeny.ai/job/strategic-partnerships-manager-cosine-london-43kyjed5b9qe) — London, United Kingdom - [ML Systems Engineer - Model Training and Infrastructure (SWE-focused LLMs)](https://feeny.ai/job/ml-systems-engineer-model-training-and-infrastructure-swe-focused-llms-cosine-2zc7z5va8axx) — London, United Kingdom - [Technical GTM Lead](https://feeny.ai/job/technical-gtm-lead-cosine-london-jqsgvabjdw8w) — London, United Kingdom - [Expression of Interest](https://feeny.ai/job/expression-of-interest-cosine-london-e81t81xzwf0e) — London, United Kingdom