Machine Learning Researcher working with a diverse team to integrate ML techniques into fusion technology. Collaborating with scientists and engineers to drive innovative energy solutions.
About the role
- Data & AI Scientist designing solutions using foundation models to address complex business challenges. Collaborating across teams to integrate AI into production environments, focusing on performance and mentorship.
Responsibilities
- Design and implement solutions using foundation models (e.g., GPT, PaLM, Claude, Gemini) for tasks such as summarization, Q&A, classification, and generation.
- Evaluate model performance, fine-tune pre-trained models, and apply prompt engineering techniques.
- Build and deploy autonomous agents capable of reasoning, planning, and interacting with APIs or tools to complete tasks.
- Develop and deploy supervised and unsupervised ML models using scalable pipelines.
- Integrate ML models into production environments using CI/CD and containerization tools.
- Build robust, modular Python applications for data processing, model training, and inference.
- Collaborate with Machine Learning Engineers to ensure seamless integration of AI solutions.
- Mentor junior data scientists and engineers in AI techniques and best practices.
Requirements
- Master’s or PhD in Computer Science, AI, Data Science, or a related field or equivalent experience
- 3 or more years of experience in data science or AI roles, with hands-on experience in foundation models and agent-based systems
- Proficiency in Python and ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers)
- Experience with LangChain, AutoGen, or similar agentic frameworks
- Strong understanding of cloud platforms (GCP preferred)
- Excellent communication and leadership skills
Benefits
- A generous pension contribution of up to 15%
- An annual performance-related bonus
- Share schemes including free shares
- Benefits you can adapt to your lifestyle, such as discounted shopping
- X days’ holiday, with bank holidays on top
- A range of wellbeing initiatives and generous parental leave policies
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