Machine Learning / Generative AI Consultant (Databricks)

Job description

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 ROLEAs 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 TASKSDesign 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 workflowsPartner with customers across industries (e.g., Healthcare, Finance, Retail, Startups) to solve complex business challengesBuild, scale, and optimize machine learning pipelines and data science workloadsApply MLOps best practices to deploy and productionize ML/GenAI systemsAdvise customer data teams on architecture, tooling, and best practicesContribute to thought leadership by mentoring internal ML subject matter expertsCollaborate with internal product, engineering, and developer relations teams to influence product direction and roadmapYOUR PROFILE5+ years of hands-on industry experience in data science or machine learningProven 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 PyTorchExperience deploying production-grade ML or GenAI solutions on AWS, Azure, or GCPGraduate degree in a quantitative field (Computer Science, Engineering, Statistics, etc.) or equivalent practical experienceStrong communication skills with the ability to explain complex technical concepts to both technical and non-technical audiencesPassion for collaboration, continuous learning, and delivering business value through ML Nice to have: Experience working with

Databricks and Apache SparkFamiliarity with GenAI tooling such as LangChain, HuggingFace, OpenAI APIsPrior experience in customer-facing or consulting environmentsWhat 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.