Associate-AI-ML Engineer / GenAI Engineer - Data Scientist

Quick Facts

Junior AI-Native Consultant (Onsite – Houston, TX)
Energy & Utilities focus

Description

Capgemini is seeking an enthusiastic and driven Junior AI-Native Consultant to join the Energy & Utilities sector team. The role is designed for emerging talent passionate about leveraging Artificial Intelligence to solve complex industry challenges, including optimizing operations, enhancing decision-making, and driving digital transformation through AI/ML.

Your Role

• Collaborate with senior consultants and client teams to identify business challenges and opportunities for AI-driven solutions in the Energy & Utilities sector.
• Assist in the design, development, and deployment of AI/ML models, including Generative AI and Predictive AI solutions.
• Support data collection, cleaning, and preprocessing activities for AI initiatives.
• Work with cloud technologies (Azure, AWS, GCP) and their AI/ML services.
• Utilize platforms such as Databricks, PySpark, and modern AI frameworks.
• Develop agentic AI workflows and intelligent agents to automate tasks and improve operational efficiency.
• Participate in client workshops and presentations, articulating technical concepts to diverse stakeholders.
• Contribute to project documentation, reports, and client deliverables.
• Develop reusable assets, demos, and solution accelerators.
• Stay current with emerging AI technologies and industry trends within the Energy & Utilities landscape.
• Foster a collaborative environment by sharing knowledge and best practices.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related quantitative field.
• Minimum of 15 months of professional (non-internship) work experience in data science, AI, or machine learning roles.
• Demonstrable background in the Energy & Utilities sector, specifically with OFSC (Oracle Field Service Cloud), Oil & Gas, or general Utilities industry knowledge.
• Foundational knowledge of Artificial Intelligence, Machine Learning, and Deep Learning concepts.
• Proficiency in at least one AI-centric programming language (e.g., Python).
• Experience with Generative AI concepts (GPT, Claude, LLMs).
• MLOps experience, including model deployment and monitoring.
• LangChain and Retrieval-Augmented Generation (RAG) concepts.
• REST APIs, JSON, Authentication, and integration patterns.
• Deployment tools (Azure DevOps, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS CloudFormation, CodeDeploy).
• Data engineering principles, including SQL and NoSQL databases (e.g., MySQL, MongoDB, Redis).
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent communication, presentation, and interpersonal skills for client-facing situations.
• Ability to quickly adapt to new technologies and thrive in a fast-paced, evolving environment.

Preferred Qualifications

• Familiarity with industry-specific tools such as Seeq and historians (e.g., PHD).
• Experience with data visualization tools and techniques.
• Experience with Machine Learning frameworks (TensorFlow, PyTorch, scikit-learn).
• Experience with NLP, computer vision, and graph database technology (Neo4J, Ontotext).
• Experience with JIRA / Confluence.
• Prior project or internship experience in a consulting environment.

Benefits

• Comprehensive, non-negotiable benefits package for regular, full-time employees.
• In the U.S. and Canada, benefits may include: Paid time off (vacation 12–25 days depending on grade, company paid holidays, personal days, sick leave), medical/dental/vision coverage (or provincial healthcare coordination in Canada), retirement savings plans (e.g., 401(k) or RRSP), life and disability insurance, employee assistance programs, and other benefits per local policy and eligibility.