Machine Learning / Generative AI Consultant (Databricks)
Confirmed on the employer's own hiring board on Oct 5, 2026. First seen by Alion on Sep 7, 2026. Capgemini scores B on the Alion truth index.
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.
YOUR ROLE
As part of the Machine Learning (ML) Practice team, you will work at the forefront of Large Language Model (LLM) innovation, partnering directly with customers to design, build, and deploy advanced ML and GenAI solutions. You will contribute to strategic initiatives, collaborate cross-functionally, and help shape the future of ML and AI adoption across industries.
YOUR TASKS
- Design and develop LLM-powered solutions on customer data, including Retrieval-Augmented Generation (RAG) systems, natural language interfaces for structured data (e.g., Text2SQL), content generation workflows
- Partner with customers across industries (e.g., Healthcare, Finance, Retail, Startups) to solve complex business challenges
- Build, scale, and optimize machine learning pipelines and data science workloads
- Apply MLOps best practices to deploy and productionize ML/GenAI systems
- Advise customer data teams on architecture, tooling, and best practices
- Contribute to thought leadership by mentoring internal ML subject matter experts
- Collaborate with internal product, engineering, and developer relations teams to influence product direction and roadmap
YOUR PROFILE
- 5+ years of hands-on industry experience in data science or machine learning
- Proven experience building Generative AI applications (e.g., RAG, agents, Text2SQL, fine-tuning, LLM deployment)
- Strong proficiency with ML and data science tools such as pandas, scikit-learn, MLflow, and PyTorch
- Experience deploying production-grade ML or GenAI solutions on AWS, Azure, or GCP
- Graduate degree in a quantitative field (Computer Science, Engineering, Statistics, etc.) or equivalent practical experience
- Strong communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences
- Passion for collaboration, continuous learning, and delivering business value through ML
Nice to have:
- Experience working with Databricks and Apache Spark
- Familiarity with GenAI tooling such as LangChain, HuggingFace, OpenAI APIs
- Prior experience in customer-facing or consulting environments
What you will love about working here?
- We care about all our employees and want them to feel as comfortable as possible. That's why we offer them health insurance from the first days, regardless of the probationary period.
- The gift from the company - Christmas holidays from 25 December to 31 December.
- Сooperation with Superhumans center and Veteran HUB. Capgemini Engineering has supported the launch of psychological rehabilitation department of Superhumans. Our team also donnated over UAH 500 000 prosthetics for three Ukrainian defenders. Currently, we support psychological counseling provided by the Veteran Hub, and we have implemented a internal policy making the company friendly to military and veterans with the assistance of the Hub.
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.