JOB DETAILS
Senior AI/ML Engineer
CompanyFortive
LocationIndia
Work ModeOn Site
PostedSeptember 8, 2026
About The Company
Fortive’s essential technology makes the world safer and more productive. We accelerate transformation in high-impact fields like workplace safety, build environments, and healthcare.
We are a global industrial technology innovator with a startup spirit. Our forward-looking companies lead the way in healthcare sterilization, industrial safety, predictive maintenance, and other mission-critical solutions. We’re a force for progress, working alongside our customers and partners to solve challenges on a global scale, from workplace safety in the most demanding conditions to advanced technologies that help providers focus on exceptional patient care.
We are a diverse team 10,000 strong, united by a dynamic, inclusive culture and energized by limitless learning and growth. We use the proven Fortive Business System (FBS) to accelerate our positive impact.
At Fortive, we believe in you. We believe in your potential—your ability to learn, grow, and make a difference.
At Fortive, we believe in us. We believe in the power of people working together to solve problems no one could solve alone.
At Fortive, we believe in growth. We’re honest about what’s working and what isn’t, and we never stop improving and innovating.
Fortive: For you, for us, for growth.
Ready to move your career forward? Find out more at careers.fortive.com.
Recruitment fraud alert: Fortive has been made aware of candidates receiving fraudulent job opportunities from unauthorized recruiting agencies or people impersonating Fortive leaders. We take this matter very seriously and are taking all appropriate measures to address this. Learn more: https://careers.fortive.com/recruitment_fraud
About the Role
Senior AI/ML Engineer
About the Role
We're seeking a Senior AI/ML Engineer to lead the design, development, and deployment of ML/AI solutions, agents, and data automations across our AWS-based analytics platform. In this role, you'll architect end-to-end ML systems, set technical direction, mentor junior engineers and analysts, and drive best practices in MLOps and ML infrastructure. This is a high-impact role for an experienced engineer who can own complex, ambiguous problems and deliver production-grade machine learning and AI agent solutions.
Key Responsibilities
- Architect, train, evaluate, and optimize machine learning models, owning the full model lifecycle from experimentation to production
- Design and build AI agents and automated workflows using Amazon Quick and AWS orchestration tools
- Define and implement efficient ML workflows, optimizing for performance, scalability, and cost
- Architect and maintain serverless data pipelines using AWS Glue, Step Functions, Lambda, and EventBridge Scheduler
- Lead the design of our analytics service engine for ingesting, transforming, and querying data across S3 storage (Excel/CSV files, Delta Tables, library files)
- Establish MLOps practices, CI/CD pipelines, and infrastructure standards for the team
- Integrate with external systems (e.g., SAP, Salesforce) and design robust data-sourcing strategies
- Design and build REST APIs and model-serving infrastructure for production workloads
- Mentor junior engineers, conduct code reviews, and set technical standards
- Partner with cross-functional stakeholders to translate business needs into ML solutions
Required Technical Skills
- Programming: Expert in Python with a track record of writing clean, well-tested, production-grade code
- ML Frameworks: Strong, hands-on experience with PyTorch, TensorFlow, and scikit-learn
- Model Development: Deep understanding of model training, evaluation, inference, and optimization for efficient ML at scale
- AI Agents & Automation: Proven experience building AI agents and automated workflows; proficient with Amazon Quick
- MCP & Tool Integration: Experience building and integrating Model Context Protocol (MCP) servers to connect LLMs and AI agents with external tools, data sources, and services
- APIs & Serving: Strong experience designing REST APIs and deploying/serving ML models in production
- Cloud & Infrastructure: Solid experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker)
- MLOps & Tooling: Proficient with Git, CI/CD pipelines, and ML infrastructure best practices
Familiarity with Our Architecture
Our team's analytics platform is built on AWS. Deep familiarity with the following components is expected, and you'll help shape how we use and evolve them:
- Orchestration & Compute: AWS Glue, AWS Step Functions, AWS Lambda, EventBridge Scheduler
- Storage & Data: S3 (CSV/Excel, Delta Tables, library files), Glue Data Catalog, Glue Crawler
- Query & Analytics: Amazon Athena
- AI & Automation: Amazon Quick
- Integration: External systems such as SAP and Salesforce
- Notifications: Amazon SNS and Amazon SES for alerting and email
- Infrastructure & Security: AWS IAM, AWS Secrets Manager, CloudWatch, AWS Systems Manager (for environment parameters)\
- Source Control & CI/CD: Bitbucket for version control, pull request workflows, and pipeline-based deployments
Core Competencies
- Problem-Solving: Independently solves complex, ambiguous ML and automation challenges and designs scalable solutions
- Technical Leadership: Sets technical direction, drives architecture decisions, and mentors junior engineers
- Collaboration: Leads cross-functional initiatives and owns the delivery of significant components end-to-end
- Continuous Improvement: Champions MLOps, software engineering best practices, and ML infrastructure across the team
- Code Quality: Sets and enforces high standards through clean, testable code, rigorous reviews, and robust version control
Key Skills
PythonPyTorchTensorFlowScikit-learnAWSMLOpsAI AgentsREST APIsDockerGitCI/CDData PipelinesAmazon QuickModel Context ProtocolSystem ArchitectureMentorship
Categories
TechnologyData & AnalyticsSoftwareEngineering
Job Information
📋Core Responsibilities
The Senior AI/ML Engineer will architect, train, and deploy end-to-end machine learning models and AI agents within an AWS-based analytics platform. They will also lead technical direction, establish MLOps best practices, and mentor junior team members to ensure high-quality production-grade solutions.
📋Job Type
full time
📊Experience Level
5-10
💼Company Size
8588
📊Visa Sponsorship
No
💼Language
English
🏢Working Hours
40 hours
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