Informacje o stanowisku

We’re hiring on behalf of one of London’s leading SaaS scale-ups — a company at the forefront of AI, data analytics, and next-generation technology. This is an opportunity to join an organisation that has embedded AI and machine learning into its core products for over a decade, long before it became a trend.

Our client is a trusted Enterprise SaaS provider, empowering some of the world’s largest corporations — including several FAANG companies — through cutting-edge predictive analytics and integrative AI solutions. They continuously explore and adopt the latest innovations to stay ahead in a fast-evolving tech landscape.

As a Senior/Expert ML or Data Engineer, you’ll play a key role in shaping the future of AI-driven products — designing and maintaining advanced data infrastructure and ML pipelines, including solutions based on Large Language Models (LLMs). This role combines deep data engineering skills, solid ML knowledge, and a strategic mindset, with opportunities to lead projects, mentor others, and drive innovation.

What we expect

• 5+ years of hands-on experience in designing, building, and maintaining complex data pipelines and data warehouse solutions in production environments
• Expert-level proficiency in Spark (PySpark and/or Scala), Python, SQL, and modern ETL/ELT frameworks
• Deep knowledge of data modeling (e.g. star schema, dimensional models) and data warehousing principles
• Strong understanding of data governance, data quality, and data security best practices, including ethical considerations in AI/LLM contexts
• Proven experience in large-scale data integration, transformation, and cleansing, including ML/LLM-ready data preparation
• Familiarity with data profiling and lineage tools
• Demonstrated ability to identify and resolve data issues and performance bottlenecks, especially in AI-related workflows
• Analytical mindset with the ability to turn complex data into scalable, actionable technical solutions—particularly for ML/LLM performance
• Excellent communication skills, both technical and business-oriented, including articulating AI model limitations and implications
• Strong collaboration skills, especially in cross-functional teams implementing new AI/LLM technologies
• Self-driven and adaptive, with a demonstrated passion for learning and applying new technologies in the AI/LLM space
• High attention to detail to ensure data accuracy and integrity critical to AI outcomes
• Proven ability to produce clear technical documentation, including for ML/LLM development and deployment processes

Technical requirements

• Python (expert) + Java/Scala; familiar with NLP & LLM libraries
• SQL (advanced) – complex queries, AI/ML workflows
• Data Modeling – scalable models for large AI datasets
• ETL/ELT – modern frameworks for ML data pipelines
• Big Data – Spark & tools for large-scale processing
• Cloud – experience with AWS or GCP or Azure, incl. ML/LLM services

Employment agency entry number 47

this job offer is intended for people over 18 years of age

What we offer

• Innovative Work – Engage in cutting-edge AI, ML, and LLM projects with real-world impact
• Modern Tech Environment – Work with the latest tools and technologies in a fast-evolving landscape
• Expert Team – Collaborate with top specialists in a culture that values knowledge-sharing and experimentation
• Supportive Culture – Join a team-oriented environment where your input truly matters
• Growth & Development – Access continuous learning and career advancement in a growing organisation
• Meaningful Impact – Help shape next-gen AI solutions used by global industry leaders

Your tasks

• Design, build, and maintain scalable data pipelines using Spark, Python, and ETL tools to support advanced analytics and machine learning models, including LLMs
• Develop and maintain data warehouses and models that ensure data quality, consistency, and performance, tailored to AI-driven use cases
• Collaborate with Data Scientists to develop, test, and deploy machine learning solutions, including LLM integration and productionization
• Engineer robust data infrastructure for handling large, complex datasets, including unstructured and semi-structured data essential for AI training and deployment
• Evaluate and experiment with new ML models, frameworks, and LLMs to assess applicability in business products
• Troubleshoot data and infrastructure issues, resolve performance bottlenecks, and implement optimization strategies, especially for large-scale AI deployments
• Define and promote best practices in data modeling, pipeline architecture, and ML workflow design, with a focus on advanced AI integration
• Maintain clear technical documentation for data workflows, models, and ML processes, including LLM-related implementations
• Work closely with analysts, scientists, and engineering teams to gather requirements and deliver impactful data solutions
• Stay current with emerging trends in data engineering, ML, and generative AI, and help mentor junior team members

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