Machine Learning Engineer for Generative AI Solutions

As a Senior GenAI Solutions Machine Learning Engineer, you will lead the development and implementation of advanced data engineering solutions to support the deployment and optimization of Generative AI models. Your role will involve leveraging your extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of General Artificial Intelligence (GenAI) applications. Key Responsibilities Architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production generative AI systems. Build and maintain data engineering solutions on cloud platforms using hyperscaler services. Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes). Understand indexing and vectorization to use with Generative AI prompt engineering. Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models. Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI. Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations. Required Skills Bachelor's degree in computer science, data engineering, or a related field with 5+ years experience (Master's preferred). Proven experience in data engineering, ETL, and database management, QL and data manipulation languages. Proficiency in Azure, Python, Java, or Scala. Experience with data warehousing platforms (e.g., Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark). Experience with highly scalable data stores, data lake, data warehouse, lakehouse, and unstructured datasets. Benefits Flexible work Healthcare including dental, vision, mental health, and well-being programs Financial well-being programs such as 401(k) and Employee Share Ownership Plan Paid time off and paid holidays Paid parental leave Family building benefits like adoption assistance, surrogacy, and cryopreservation Social well-being benefits like subsidized back‑up child/elder care and tutoring Mentoring, coaching and learning programs Employee Resource Groups Disaster Relief Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodations do not pose an undue hardship. Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Click the following link for more information on your rights as an Applicant Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini. #J-18808-Ljbffr Capgemini