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 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 LLMsDevelop and maintain data warehouses and models that ensure data quality, consistency, and performance, tailored to AI-driven use casesCollaborate with Data Scientists to develop, test, and deploy machine learning solutions, including LLM integration and productionizationEngineer robust data infrastructure for handling large, complex datasets, including unstructured and semi-structured data essential for AI training and deploymentEvaluate and experiment with new ML models, frameworks, and LLMs to assess applicability in business productsTroubleshoot data and infrastructure issues, resolve performance bottlenecks, and implement optimization strategies, especially for large-scale AI deploymentsDefine and promote best practices in data modeling, pipeline architecture, and ML workflow design, with a focus on advanced AI integrationMaintain clear technical documentation for data workflows, models, and ML processes, including LLM-related implementationsWork closely with analysts, scientists, and engineering teams to gather requirements and deliver impactful data solutionsStay current with emerging trends in data engineering, ML, and generative AI, and help mentor junior team memberswhat we expect
5+ years of hands-on experience in designing, building, and maintaining complex data pipelines and data warehouse solutions in production environmentsExpert-level proficiency in Spark (PySpark and / or Scala), Python, SQL, and modern ETL / ELT frameworksDeep knowledge of data modeling (e.g. star schema, dimensional models) and data warehousing principlesStrong understanding of data governance, data quality, and data security best practices, including ethical considerations in AI / LLM contextsProven experience in large-scale data integration, transformation, and cleansing, including ML / LLM-ready data preparationFamiliarity with data profiling and lineage toolsDemonstrated ability to identify and resolve data issues and performance bottlenecks, especially in AI-related workflowsAnalytical mindset with the ability to turn complex data into scalable, actionable technical solutions—particularly for ML / LLM performanceExcellent communication skills, both technical and business-oriented, including articulating AI model limitations and implicationsStrong collaboration skills, especially in cross-functional teams implementing new AI / LLM technologiesSelf-driven and adaptive, with a demonstrated passion for learning and applying new technologies in the AI / LLM spaceHigh attention to detail to ensure data accuracy and integrity critical to AI outcomesProven ability to produce clear technical documentation, including for ML / LLM development and deployment processesTechnical requirements
Python (expert) + Java / Scala; familiar with NLP & LLM librariesSQL (advanced) – complex queries, AI / ML workflowsData Modeling – scalable models for large AI datasetsETL / ELT – modern frameworks for ML data pipelinesBig Data – Spark & tools for large-scale processingCloud – experience with AWS or GCP or Azure, incl. ML / LLM servicesEmployment agency entry number 47
this job offer is intended for people over 18 years of age