Location: Brasil (Remote/Hybrid) | Experience: 6+ Years | Core Stack: Python, PySpark, Azure Databricks, LLMs, MLflow | Workplace Type: Remote
The Opportunity
KPIT is seeking a high-caliber Senior Data Scientist / AI Engineer to architect and deliver end-to-end, production-grade AI and Machine Learning solutions. This is not just a research role;
it is a hands-on engineering position designed for a specialist who can bridge the gap between complex mathematical modeling and scalable cloud deployment. You will lead the development of next-generation AI agents and scalable data pipelines on Azure, turning massive datasets into intelligent, autonomous workflows that drive real business value.
Technical Leadership & AI Engineering
* End-to-End AI Ownership: Take full accountability for the AI lifecycle—from initial problem definition and data discovery to the deployment and monitoring of production-grade models.
* Agentic AI & Generative AI: Spearhead the development of advanced Agentic AI workflows, implementing multi-step reasoning, tool usage, and autonomous decision-making capabilities using modern GenAI frameworks.
* Scalable Data Engineering: Architect and maintain high-performance data pipelines using PySpark and Spark within the Azure Databricks ecosystem.
* MLOps & Lifecycle Management: Implement robust MLOps practices using MLflow to track experiments, manage deployments, and ensure seamless model versioning.
* Production Reliability: Design sophisticated monitoring systems to track model performance, detect data drift, and ensure the long-term reliability and integrity of AI in live environments.
Technical Expertise Required (Must Have)
* 5–6 years of professional experience in Data Science, Machine Learning, or AI Engineering.
* Advanced Python & SQL: Expert-level coding skills for data manipulation, algorithm development, and database interaction.
* Big Data Ecosystem: Proven hands-on experience with PySpark, Spark, and Azure Databricks .
* Cloud Native AI: Strong experience delivering and scaling ML solutions within the Microsoft Azure environment.
* Generative AI Expertise: Practical experience with LLMs and AI Agent frameworks (e.G., LangChain or Semantic Kernel ).
* MLOps Proficiency: Solid understanding of the ML lifecycle, including feature engineering, evaluation techniques, and MLflow .
* Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field.
The Differentiators
* Advanced Orchestration: Experience building complex, multi-agent systems that interact with external tools/APIs.
* Architectural Depth: Ability to design not just the model, but the entire data-to-inference architecture.
* Mentorship: A track record of elevating engineering standards and mentoring junior data scientists.
Who You Are
* An Architect: You don't just build models;
you build scalable, production-ready systems.
* A Lifelong Learner: You stay at the forefront of the rapidly evolving GenAI and Agentic AI landscape.
* A Business Translator: You can translate vague business problems into precise technical requirements and measurable AI outcomes.
The Reward
* Cutting-Edge Tech: Opportunity to work with the latest in Agentic AI and Large Language Models.
* Competitive Compensation: Salary packages that recognize your specialized AI/ML expertise.
* Health & Wellness: Comprehensive medical and dental insurance.
* Vouchers: Competitive VR/VA package and more.
* Career Growth: Clear progression and leadership opportunities within a global technology leader.
* Impact: Drive the AI-led digital transformation of the global automotive and mobility ecosystem.
About KPIT
KPIT is a global partner to the automotive and mobility ecosystem, delivering end-to-end engineering, data, and AI-led digital transformation solutions to leading OEMs and Tier-1 suppliers. We help shape the future of mobility by integrating intelligence into every aspect of the vehicle and the driving experience.