Senior Machine Learning Engineer

In this role you will lead production-grade AI initiatives, spanning data ingestion to deployment, ensuring reliable, reproducible models. You join a global AI team applying LLMs and agentic workflows to real-world solutions, driving business impact. You will tackle end-to-end AI development, data infrastructure, and orchestration to deliver scalable, domain-specific AI systems. This is an opportunity to shape AI-enabled products at the intersection of science and industry.

• Competitive salary
• Bonus scheme
• 22 days annual leave + holiday buy/sell
• Hybrid work with 2 days at home
• Company pension with employer contribution
• Unmind wellbeing app access

• LLM/NLP model development: deploy and fine-tune domain-specific LLMs; build evaluation and benchmarking pipelines; apply reinforcement learning and knowledge representation to end-to-end problems
• Data infrastructure: collaborate to build data pipelines for ingestion, transformation, versioning, and labeling; ensure reproducible data loops
• AI workflow design & orchestration: orchestrate multi-model AI solutions to achieve state-of-the-art results; partner with production and software teams; architect multi-model agentic workflows (function calling, tool usage, RAG, code interpreters) in production systems
• Leadership: provide technical leadership and mentorship to junior engineers to foster learning and innovation

• Master’s or Ph.D in Computer Science, Mathematics, Physics, Electrical Engineering, or related technical disciplines
• Strong programming skills in C, C++, R, Java, or Python
• Advanced understanding of LLM/VLM architectures, post-training methods, and evaluation pipelines
• Experience with data and system engineering for large-scale model workflows
• Proven experience with TensorFlow or PyTorch DL frameworks
• Experience with tools: Cursor, Windsurf, Trae, Gemini CLI, Claude Code, or Codex
• Experience deploying LLMs to real-world use cases is a plus
• Strong communication and project management skills
• Enthusiastic about learning and adapting to new challenges

• problem-solving mindset
• effective communication with stakeholders
• leadership and mentorship
• LLM/VLM architectures
• fine-tuning and RL for models
• data pipelines and data versioning