Interested in this AI/ML Engineer role at Gordian?
Apply Now →Skills & Technologies
About This Role
The Sr. Director, Platform \& AI Infrastructure leads the platforms that power Gordian's products and our AI transformation: cloud infrastructure, data platforms, ML/AI infrastructure, incident response, and observability.
This is a builder role. You'll stand up the AI platform that our product and engineering teams build on, modernize how we run production, and establish the incident response and observability programs that scale with us.
Key responsibilities
- AI platform and production ML. Own the AI/ML platform: GPU capacity strategy, model serving and inference latency, training and fine\-tuning infrastructure, MLOps and evaluation pipelines, vector and feature stores, and the RAG and agentic patterns our product teams build on. Partner with product engineering and architecture on build\-vs\-buy decisions across foundation model providers and open\-source.
- Incident and observability management. Build out the incident response program: on\-call structure, severity definitions, incident command, communication standards, postmortems, and follow\-through on systemic fixes. Develop the observability stack across metrics, logs, traces, and synthetics. Set SLOs and report against them.
- Cloud infrastructure. Operate the Azure and OCI footprint. Infrastructure\-as\-code, capacity planning, and reliability across CPU and GPU workloads.
- Data platforms. Operations, performance, HA/DR, and roadmap for Oracle, SQL Server, MongoDB, and similar.
- Communication. Brief executives on reliability and risk. Lead internal communication during incidents. Speak to customers when major incidents affect them.
- People. Lead a globally distributed team of managers and senior ICs. Maintain a strong culture and leadership bench.
Required
- 10\+ years in platform engineering, SRE, infrastructure, or AI/ML infrastructure, with 5\+ leading teams.
- Production experience running ML/AI workloads at scale, including GPU infrastructure, model serving, MLOps, or LLM/inference platforms.
- Familiarity with the modern AI stack: vector databases, RAG, agent frameworks, evaluation, and the build\-vs\-buy tradeoffs across foundation model providers and open\-source.
- Built or rebuilt an incident response or observability program at scale.
- Measurable reliability improvements (MTTR, availability, change failure rate) in a cloud environment.
- Effective communicator with executives, the Board, customers, and the company during incidents.
- Zero\-trust and modern identity platforms.
Fortive Corporation Overview
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.
About Gordian
Gordian is the world’s leading provider of facility and construction cost data, software and services for all phases of the building lifecycle. A pioneer of Job Order Contracting (JOC), Gordian’s offerings also include our proprietary RSMeans data and Sightlines Facility Intelligence solutions. From planning to design, procurement, construction and operations, Gordian’s solutions help clients maximize efficiency, optimize cost savings and increase building quality. Gordian is a part of the international business group Fortive, with 26,000 people employed worldwide.We offer an excellent benefits package including medical, dental, vision, life and LTD insurance, HSA, and a 401(k) retirement plan. EOE/AA/M/F/Vets/Disabled.
We Are an Equal Opportunity Employer. Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at [email protected].
Bonus or Equity
This position is also eligible for bonus as part of the total compensation package.
Pay Range
The salary range for this position (in local currency) is 133,600\.00 \- 248,500\.00
Gordian is the world’s leading provider of facility and construction cost data, software and services for all phases of the building lifecycle. A pioneer of Job Order Contracting (JOC), Gordian’s offerings also include our proprietary RSMeans data and Sightlines Facility Intelligence solutions. From planning to design, procurement, construction and operations, Gordian’s solutions help clients maximize efficiency, optimize cost savings and increase building quality. Gordian is a part of the international business group Fortive, with 26,000 people employed worldwide.We offer an excellent benefits package including medical, dental, vision, life and LTD insurance, HSA, and a 401(k) retirement plan. EOE/AA/M/F/Vets/Disabled.
We Are an Equal Opportunity Employer. Fortive Corporation and all Fortive Companies are proud to be equal opportunity employers. We value and encourage diversity and solicit applications from all qualified applicants without regard to race, color, national origin, religion, sex, age, marital status, disability, veteran status, sexual orientation, gender identity or expression, or other characteristics protected by law. Fortive and all Fortive Companies are also committed to providing reasonable accommodations for applicants with disabilities. Individuals who need a reasonable accommodation because of a disability for any part of the employment application process, please contact us at [email protected].
The salary range for this position (in local currency) is 133,600\.00 \- 248,500\.00This position is also eligible for bonus as part of the total compensation package.
Salary Context
This $133K-$248K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Gordian, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($191K) sits 13% below the category median. Disclosed range: $133K to $248K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Gordian AI Hiring
Gordian has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $248K - $248K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.