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
Skills Required
- Expert in Python with production-grade, well-tested code experience
- Hands-on experience with PyTorch
- Hands-on experience with TensorFlow
- Hands-on experience with scikit-learn
- Proven experience building AI agents and automated workflows (Amazon Quick)
- Experience building and integrating Model Context Protocol (MCP) servers
- Designing REST APIs and deploying/serving ML models in production
- Experience with cloud platforms (AWS; familiarity with Azure and GCP)
- Containerization experience (Docker)
- MLOps, Git, and CI/CD pipeline experience
- Experience with AWS Glue, Step Functions, Lambda, and EventBridge Scheduler
- Experience with S3, Delta Tables, Glue Data Catalog, Glue Crawler, and Amazon Athena
- Integration experience with external systems such as SAP and Salesforce
- Familiarity with AWS IAM, Secrets Manager, CloudWatch, and Systems Manager
- Experience with Bitbucket and pull-request based CI/CD workflows
- Proven ability to mentor junior engineers, conduct code reviews, and set technical standards
Fortive Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fortive and has not been reviewed or approved by Fortive.
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Parental & Family Support — Parental leave is fully paid for 12 weeks for all parents, with fertility coverage via Progyny and generous adoption/surrogacy support. Backup child and adult care plus inclusive eligibility extend support across diverse family structures.
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Healthcare Strength — Multiple PPO and HSA medical options include telemedicine and second-opinion services, alongside robust mental-health access through Spring Health with no‑cost therapy sessions. The breadth of medical and behavioral health resources is highlighted as a strength.
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Retirement Support — The 401(k) provides a competitive employer match each pay period, with an additional company retirement contribution after one year of service. Financial wellness tools and an employee stock purchase plan further bolster long‑term savings.
Fortive Insights
What We Do
Fortive’s essential technology makes the world stronger, safer, and smarter. We accelerate transformation across a broad range of applications including environmental, health and safety compliance, industrial condition monitoring, next-generation product design, and healthcare safety solutions. We are a global industrial technology innovator with a startup spirit. Our forward-looking companies lead the way in software-powered workflow solutions, data-driven intelligence, AI-powered automation, and other disruptive technologies. 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 groundbreaking sustainability solutions. We are a diverse team 18,000 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.
