Senior AI/ML Research Engineer
ago
Location
Waterloo, London
Hybrid
Salary
Competitive
Employment Type
Contractor
Experience Level
Entry
Junior
Mid
Senior
Expert
Our Client
Global Energy Company
SPECIALTY
Upstream/Downstream, Bio-Fuels, Integrated Gas, New Energies, Chemicals, Energy and Trading
INDUSTRY
Energy
Company Size
80000+ Employees
Aubay's Take
Our client is one of the Super Major global energy companies with who are working to power progress through cleaner energy solutions. You will have the opportunity to work in a challenging but rewarding environment that is fast paced and changing fundamentally, and work towards transforming the business of a Super Major energy company to meet the ambition to be a net-zero emissions energy business by 2050, whilst delivering a world class business case that has a strong societal license to operate. In your role you will be expected to enact change and deliver value globally across business lines and geographies.
Role Summary
Aubay UK is seeking an experienced Senior AI/ML Research Engineer to join a growing Data & AI organisation focused on developing and deploying enterprise-scale Artificial Intelligence and Generative AI solutions. The successful candidate will be responsible for designing, developing, deploying, and optimising production-grade AI and Machine Learning systems that deliver measurable business value across multiple domains. Working closely with Data Engineers, DevOps teams, Product Managers, Architects, and business stakeholders, the role will focus on building scalable, reliable, and reusable AI capabilities that meet enterprise standards for performance, security, and operational excellence. This is an excellent opportunity for a highly technical AI/ML Engineer with expertise in cloud-native machine learning, GenAI, RAG architectures, and large-scale data platforms who enjoys driving innovation while delivering real-world business outcomes.
Required Skills and Experience:
- 10+ years of experience in software engineering and machine learning engineering
- Strong expertise designing and deploying large-scale AI/ML systems and architectures
- Advanced programming experience with Python and modern software engineering practices
- Experience building AI/ML solutions on Microsoft Azure
- Strong experience with Kubernetes, containerisation, and cloud-native deployments
- Experience designing and maintaining CI/CD pipelines and automated ML workflows
- Hands-on experience with Databricks, Spark, PySpark, and large-scale data processing
- Experience working with SQL and NoSQL databases
- Strong understanding of machine learning lifecycle management, monitoring, and optimisation
- Experience working in Agile, cross-functional delivery teams
- Bachelor's, Master's, or PhD in Computer Science, Engineering, Statistics, or a related discipline
Desired Skills and Experience:
- Experience developing Generative AI solutions using Azure OpenAI and LangChain
- Experience building enterprise Retrieval-Augmented Generation (RAG) solutions
- Experience designing autonomous AI Agent and multi-agent architectures
- Experience developing Text-to-SQL and natural language query solutions
- Knowledge of Infrastructure as Code using Terraform and Helm
- Experience with Kafka, event-driven architectures, and distributed systems
- Experience with AWS SageMaker, Vertex AI, or other cloud AI platforms
- Knowledge of React, .NET, or C# development
- Strong understanding of MLOps best practices and AI governance
- Commercial awareness and ability to align technical solutions with business objectives
Roles and Responsibilities:
- Design, develop, and deploy enterprise-scale AI and Machine Learning solutions
- Lead end-to-end AI/ML delivery from experimentation through production deployment and support
- Build and maintain robust ML pipelines for feature engineering, training, evaluation, deployment, and monitoring
- Develop scalable Generative AI and Large Language Model (LLM) solutions
- Design and implement enterprise Retrieval-Augmented Generation (RAG) architectures
- Develop autonomous AI agents and orchestration frameworks to solve business problems
- Automate the full AI/ML lifecycle, including model training, testing, deployment, monitoring, and optimisation
- Collaborate with Product Owners and business stakeholders to translate requirements into technical solutions
- Work closely with Data Engineering and DevOps teams to improve platform reliability and deployment efficiency
- Optimise AI solutions for scalability, performance, cost, and operational resilience
- Contribute to the evolution of AI engineering standards, best practices, and reusable frameworks
- Conduct research into emerging AI technologies and assess their applicability to business challenges
- Support technical mentoring, knowledge sharing, and AI community initiatives
- Ensure solutions meet enterprise standards for governance, security, quality, and compliance
- Drive continuous improvement across AI platforms, engineering practices, and delivery processes
This site uses cookies 🍪
We use cookies and similar technologies to give you a personalised browsing experience, personalised advertising and to analyse our web traffic. Click 'Accept' if you'd like to allow all cookies. Alternatively, you can choose which types of cookies you'd like to accept or disable by clicking 'Reject' below. For more information, please see our Cookie Policy.