Cosine jobs

Cosine is seeking an Applied ML Technical Lead to join their UK AI lab, focusing on developing and deploying advanced AI capabilities for UK Defence and national security organizations. This is a hands-on technical leadership role where you will guide the technical direction and day-to-day progress of applied ML projects, translating research into operational capabilities. You will work across machine learning development, deployment, and customer-facing technical delivery, potentially involving training and evaluating models on complex sensor data, and engaging with Defence stakeholders to understand needs and shape priorities. The role requires coordinating ML researchers, software engineers, and infrastructure teams, identifying and resolving technical risks, and establishing clear evaluation criteria to demonstrate progress through measurable improvements and working capabilities.

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Cosine is developing autonomous software-engineering systems for organizations that prioritize reliability, security, and control. Our Lumen Enterprise models are designed to understand and modify real codebases, utilizing tools, running tests, and producing maintainable software. We are seeking a Machine Learning Engineer to enhance and train these models across the entire training stack, including pre-training, supervised fine-tuning, and reinforcement learning. This role offers exposure to all facets of the model training lifecycle, from performance profiling to implementing new RL algorithms, and requires a hands-on approach with a focus on software quality.

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We are seeking an ML Systems Engineer to contribute to the training of our Lumen LLMs, which are based on open-source software engineering models. This role is interdisciplinary, involving the development and deployment of reinforcement learning training environments, working with large-scale synthetic data pipelines, and building an ML platform for training large models in distributed settings. The goal is to train models that not only provide correct answers but also write readable, maintainable code aligned with architectural patterns. This position is ideal for someone passionate about the evolving landscape of coding agents, where data, RL environments, and opinionated reward functions are shaping future SWE model standards.

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