Overview
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.
Pay / Benefits
- 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
Responsibilities
- 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
Key requirements
- 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
Senior Machine Learning Engineer in Crawley employer: CGG
At Viridien, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation. Our commitment to employee growth is evident through continuous training opportunities and a supportive environment that encourages professional development. Located in a vibrant area, our team enjoys a healthy work-life balance, competitive benefits, and the chance to work on cutting-edge network technologies that make a real impact globally.
