Intern at Fortive

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

23 Jun, 26

Salary

0.0

Posted On

25 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, GenAI, Agentic AI, LLMs, Automation, RAG, MLOps, Vector Databases, Transformers, LangChain, LangGraph, CrewAI, Docker, CI/CD, Cloud Platforms

Industry

electrical;Appliances;and Electronics Manufacturing

Description

About the Role We are looking for highly motivated AI/ML Interns who are passionate about GenAI, Agentic AI, Machine Learning, Automation, and building real-world scalable solutions. As an intern, you will work closely with one of our three high-performing teams within Fortive Business Systems Office (FBSO): 1. Productivity AI Team (Enablement / LEAN Phase) Focused on empowering 10,000+ Fortive employees by embedding cutting-edge AI into FBS tools and workflows. You will work with: * GenAI capabilities * Agentic systems * LLM-based productivity enhancements * MCP-driven automations 2. Growth & Innovation Team (DREAM Phase) Works on zero-to-one innovations, experimentation, and shaping future AI products. You will explore: * New AI prototypes * Research-style experimentation * Early-stage product concepts * POCs leveraging LLMs, Vision Models, RAG, Agents 3. Commercialization Team (Develop / Deliver Phases) Focuses on productionizing AI solutions, MLOps, scalability, and customer-facing delivery. You will get exposure to: * Model deployment (cloud platforms) * ML pipelines * Monitoring, evaluation, and improvements * Taking AI solutions to enterprise customers Across all three teams, you will be mentored by experienced Data Scientists, ML Engineers, MLOps Engineers, and leaders working at the forefront of AI innovation at Fortive. What You Will Do During your internship, you may contribute to: * Building and evaluating GenAI and Agentic AI prototypes * Developing Python-based ML/AI pipelines * Working on RAG systems, document intelligence, and Cognitive Search * Automating workflows using AI + RPA concepts * Experimenting with leading LLMs, Vision models, and multimodal models * Supporting MLOps initiatives such as CI/CD for ML models * Collaborating with cross-functional teams to design meaningful AI capabilities * Participating in brainstorming, design sprints, and LEAN/DREAM activities under FBS * Preparing and presenting results to senior leadership This internship gives exposure to end-to-end AI product development — from idea → prototype → production. What We’re Looking For Must-Have Skills * Strong programming experience in Python * Understanding of Machine Learning fundamentals * Curiosity and willingness to learn GenAI, LLMs, AI Agents, MCP, Vector Databases * Ability to work independently and in teams * Good communication and problem-solving abilities Good-to-Have Skills (Not mandatory but an advantage) * Knowledge of LLMs, Transformers, LangChain, LangGraph, CrewAI * Experience with RAG, embeddings, vector stores * Basic MLOps exposure (Git, Docker, CI/CD) * Familiarity with cloud platforms (AWS / Azure / GCP) * Interest in DevOps + AI or RPA automation What Interns Will Gain * Direct mentorship from senior Data Scientists & MLOps engineers * Real-world experience working on enterprise-scale AI problems * Hands-on exposure to advanced AI tools, frameworks, and cloud environments * Opportunity to contribute to solutions used across Fortive’s global ecosystem * End-to-end understanding of AI product lifecycle via FBS (DREAM → LEAN → Develop/Deliver) * Potential extension to 6 months & future career opportunities within Fortive Who Should Apply Students or early-career professionals in: * Computer Science * Data Science * AI/ML * Electronics * Mathematics / Statistics * Or anyone with strong Python + AI interest How to Apply Interested candidates can share: * Resume * GitHub / Portfolio (if available) * A short note on why they want to join an AI team

Responsibilities

Interns will contribute to building and evaluating GenAI and Agentic AI prototypes, developing ML/AI pipelines, and working on RAG systems and workflow automation using AI and RPA concepts. They will also support MLOps initiatives and collaborate with cross-functional teams to deliver AI capabilities.