Machine Learning Engineer - Agentic AI & Reinforcement Learning
CGG (Compagnie Générale de Géophysique)1 day ago
Crawley, United KingdomMid Level
Responsibilities
- Design and develop single-agent and multi-agent systems.
- Implement reasoning, planning, task decomposition, memory, tool-use, and agent-collaboration capabilities.
- Integrate LLMs, vision-language models, retrieval systems, and domain-specific tools.
- Experiment with foundation-model fine-tuning, supervised learning, preference optimisation, and reinforcement learning.
- Develop training environments, reward functions, graders, and feedback mechanisms.
- Design evaluations, guardrails, and monitoring approaches for agent reliability.
- Convert successful prototypes into APIs, services, and reusable software components.
Requirements
- Degree in computer science, artificial intelligence, machine learning, engineering, or a related discipline, or equivalent practical experience.
- Good Python programming skills and an understanding of software engineering practices.
- Experience building machine-learning, generative-AI, or LLM applications through employment, industry or research internships, applied research, or significant academic projects.
- Experience with PyTorch, JAX, TensorFlow, or a similar framework.
- Familiarity with agentic AI concepts including tool calling, planning, memory, and workflow orchestration.
- Understanding of reinforcement learning, preference optimisation, or sequential decision-making.
- Experience evaluating models or implementing ideas from machine-learning research.
- Familiarity with multi-agent frameworks such as LangGraph, AutoGen, or smolagents.
- Exposure to LLM fine-tuning or preference and reinforcement-learning approaches such as DPO, GRPO, RLHF, or RLAIF.
- Experience designing reward functions, graders, or agent training environments.
- Familiarity with Model Context Protocol or other tool-integration approaches.
- Exposure to training or deploying open-source language or vision-language models using GPUs, including distributed training.
- Experience applying AI to scientific, engineering, energy, or geoscience workflows is desirable.
Benefits
- Competitive salary commensurate with experience and a highly attractive bonus scheme.
- Initial 22 days of annual leave with future increases, plus flexible holiday buying and selling.
- Hybrid working with three days in the office and two days at home.
- Company pension with a generous employer contribution.
- Wellbeing Unmind app and flexible benefits with discounts including gym memberships, restaurants, and cinema tickets.
- Cycle purchase scheme and flexible private medical and dental care programmes.
- Bank Holiday Swap, relaxed dress code, and tailored learning and development programmes.
Categories
About CGG (Compagnie Générale de Géophysique)
CGG (Compagnie Générale de Géophysique), now operating as Viridien, builds geoscience software, Earth data products, and sensing/monitoring services for energy, natural resources, environmental, and infrastructure customers. Its business spans subsurface imaging, satellite imagery, and HPC/AI-enabled managed services, sold via licenses, data subscriptions, and consulting projects. Founded in 1931 and headquartered in Massy, France, it is a public company listed in Paris (EPA).