cosine - Applied ML Technical Lead, Defence
Requirements
• You'll probably have a background in applied machine learning, ML engineering, research engineering or a similarly technical role, along with experience taking ownership of complex technical work. • You should be comfortable: • Writing production-quality Python and working with modern ML frameworks such as PyTorch. • Building, training, fine-tuning and evaluating machine learning models. • Working with complex datasets, designing experiments and interpreting model performance. • Understanding the trade-offs between model performance, compute requirements, latency and deployment constraints. • Working with engineering infrastructure, including Git, containers, Linux and GPU compute. • Taking technical ownership of projects with multiple stakeholders, uncertain requirements and evolving priorities. • Communicating technical concepts clearly to researchers, engineers, senior stakeholders and operational users. • Moving between model development, customer discussions and delivery planning without losing technical depth. • Making sound technical judgements, prioritising effectively and finding practical solutions when the path forward is unclear. • Existing UK security clearance, such as SC or DV, or previous experience working in secure Defence environments. • Experience with signal processing, time-series data, sensor fusion, representation learning or machine learning applied to complex real-world datasets. • Experience with foundation models, multimodal learning or advanced model training and post-training techniques. • Experience deploying ML models to edge devices or constrained compute environments. • Familiarity with UK Defence procurement, technical assurance or the national security landscape. • Experience leading technical workstreams or working as a technical lead on customer-facing ML projects. • ___________________________________________________________________________ • WHAT SUCCESS LOOKS LIKE • In your first three months, we would expect you to: • Become the technical lead for a major applied Defence ML programme, with responsibility for its day-to-day technical progress. • Build strong working relationships with Cosine's ML researchers, engineers and key Defence customer stakeholders. • Develop a clear understanding of the existing models, datasets, technical architecture and operational objectives. • Establish a focused delivery plan with clear priorities, milestones, ownership and success measures. • Make meaningful hands-on contributions to model development, evaluation or deployment. • Identify and begin addressing the most important technical and operational blockers. • Demonstrate tangible progress to customer stakeholders and build confidence in Cosine's ability to deliver. • Longer term, you'll help take advanced ML capabilities from promising prototypes into operational use, while shaping how Cosine builds and delivers applied AI for Defence and other mission-critical organisations.
Responsibilities
• Build ML capabilities for real Defence problems • Design, build, train and evaluate machine learning models for challenging applied Defence and national security use cases. • Work on problems involving complex sensor data, signal processing, pattern recognition, classification and multimodal intelligence. • Develop and improve model architectures, training pipelines, evaluation frameworks and inference systems. • Work with real-world and synthetic datasets to improve model accuracy, robustness and generalisation. • Translate research prototypes into reliable, deployable capabilities that operate within demanding technical and security constraints. • Work closely with Cosine's ML research and engineering teams while taking direct ownership of technical outcomes. • Lead technical delivery from prototype to deployment • Own the technical direction and day-to-day progress of applied ML projects. • Turn operational objectives into concrete technical goals, experiments, milestones and success measures. • Coordinate work across ML researchers, software engineers, infrastructure teams and external stakeholders. • Identify technical dependencies, delivery risks and blockers, and help drive them to resolution. • Establish clear evaluation criteria and demonstrate progress through measurable improvements and working capabilities. • Balance hands-on engineering with the planning and coordination needed to keep complex technical work moving. • Work directly with Defence customers • Engage with technical and operational stakeholders across the UK Defence and national security ecosystem. • Understand operational challenges and identify where machine learning can make a meaningful difference. • Translate customer requirements and constraints into technical objectives, datasets, experiments and delivery plans. • Present technical progress, demonstrate working capabilities and communicate results clearly to technical and non-technical audiences. • Build trusted relationships with Defence stakeholders and act as a credible technical counterpart. • Help customers understand the practical considerations of integrating and deploying ML systems in their existing environments. • Turn research into operational capability • Help deploy ML models into real-world environments, including secure, on-premise and resource-constrained systems. • Work on model optimisation, inference performance, integration and reliability. • Develop robust approaches to evaluation, validation and continuous model improvement. • Understand data availability, access requirements, security restrictions and deployment constraints. • Establish feedback loops between operational users and Cosine's engineering teams. • Ensure that what we build is not only technically impressive, but genuinely useful to the people relying on it. • ___________________________________________________________________________
Benefits
• Some of the most important applications of AI won't be found in consumer products. They'll be in environments where information is incomplete, systems are complex, security matters and the consequences of getting things wrong are significant. • Cosine is working to bring frontier machine learning into those environments. • Doing that requires more than good models. It requires people who can understand an operational problem, build something that works, make good technical decisions, coordinate the work needed to deliver it and stay close to the customer until it creates real value. • You'll have unusual proximity to cutting-edge ML research, senior Defence stakeholders and the operational challenges that will shape the next generation of AI capabilities. • This role will suit someone who is technically strong enough to build, organised enough to lead technical delivery and curious enough to engage directly with the people using the technology. • If you enjoy being close to the research, close to customers and personally accountable for turning ambitious technology into something real, come and work with us. • Come help make frontier AI useful where it matters most. • ___________________________________________________________________________
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