This is an exciting role for a senior AI/ML Research Engineer to join a world-leading Energy Trading & Commodities company as part of their highly innovative GenAI Team.
You will be responsible for designing, developing, and deploying scalable AI/ML solutions across multiple business areas.
The role focuses on delivering production-grade machine learning systems while ensuring alignment with enterprise quality, reliability and scalability standards. You will lead end-to-end AI/ML solution development from data exploration and experimentation through to deployment, monitoring and continuous optimisation. You will work closely with cross-functional teams including data engineering, infrastructure, DevOps, and product management to translate business needs into robust, reusable machine learning architectures.
Required Qualifications & Experience
- Bachelor’s, Master’s, or PhD in a relevant discipline (Engineering, Computer Science, Statistics, or related fields)
- 10+ years of experience in software development and machine learning engineering
Core Technical Skills
- Strong expertise in designing large-scale machine learning systems and architectures
- Advanced programming skills (Python preferred) with experience in frameworks and tools such as JavaScript, Kafka, and reactive systems
- Extensive experience with cloud-based development, particularly on Azure, including AI/ML services and data platforms
- Proven experience with Kubernetes for application deployment, scaling, and monitoring
- Strong background in CI/CD pipeline design, automation, and maintenance
- Hands‑on experience with data engineering tools and storage solutions (e.g., ADLS, Spark, Databricks, SQL/NoSQL databases)
- Experience with distributed computing and big data processing frameworks such as PySpark
- Knowledge of infrastructure‑as‑code tools such as Terraform and Helm
Advanced / Specialist Expertise
- Experience building and deploying GenAI solutions using frameworks such as LangChain and Azure OpenAI
- Development of enterprise‑grade RAG (Retrieval-Augmented Generation) systems, including context engineering and multimodal data pipelines
- Design and deployment of autonomous multi‑agent systems using modern orchestration frameworks and evaluation approaches
- Experience delivering Text-to-SQL solutions and natural language interfaces for structured data environments
Additional Skills
- Strong understanding of data processing, cleansing, and handling large structured and unstructured datasets
- Solid foundation in Linux, scripting (Bash/PowerShell), and networking fundamentals
- Excellent communication skills with the ability to translate complex technical concepts into business terms
- Experience working in agile, cross‑functional, and globally distributed teams
- Continuous learning mindset with a focus on emerging technologies and innovation
Nice-to-Have
- Experience with AWS or GCP ML platforms (e.g., SageMaker, Vertex AI)
- Front‑end development (React) or backend development (.NET/C#)
- Commercial awareness and understanding of business value delivery
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