Pay
$154K–$225K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,958 postings in the last year. Stated ranges, not salaries paid.
Remote - US
Live, first seen by us 83 days agoListed location: Remote - USRead the full posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Lead and grow the AI/ML Engineering team, coordinating data scientists on joint projects
Design, deliver and operate the core AI/ML platform, including model hosting and semantic search
Run AI/ML systems in production for reliability, observability and incident response
Create processes to turn Data Science proof-of-concept code into production-grade services
Run stand-ups and capacity planning across engineering and data science
Lead and grow the AI/ML Engineering team, while coordinating execution across contributors including data scientists on collaborative projects.
Design, deliver and operate the core AI/ML platform: agent frameworks, evaluation harnesses, labeling systems, document processing systems, semantic search, knowledge bases, model hosting, and more.
Run AI/ML systems at scale in production with reliability, observability, performance, and incident response.
Create processes to ensure proof-of-concept code from Data Science can be designed as production-grade services.
Run tight, streamlined stand-ups across engineering and data science. Do capacity planning for driving predictability and velocity around delivery.
From the employer’s posting.
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$154K–$225K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,958 postings in the last year. Stated ranges, not salaries paid.
Day 83
Up longer than most. Similar jobs usually come down between day 7 and day 53.
From 7,803 similar postings that came down. Coming down is not always a hire.
11 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 3+ years specifically building AI/ML production-grade services at scale for multiple use cases. Direct co-working with data science and engineering. - Strong in Java, Scala, Rust, or similar backend languages, plus Python. - Understanding of what it takes to productize ML/AI platforms — workflows, serving, observability, reliability, and scale.
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
We're seeking a hands-on, technically deep Sr/Director of Engineering to lead our ML Engineering team! You will manage and grow a team of engineers who build and own the core AI/ML platform for the company, and running it at massive scale. You will also serve as a key thought partner to our Chief AI Officer, bridging the gap between data science proof-of-concepts and scalable, production-grade services.
The ideal candidate blends AI/ML engineering depth with applied data science fluency. You understand what it takes to productize AI/ML capabilities — serving, observability, reliability, and scale — and you're fluent enough in data science concepts to anticipate platform needs and influence upstream design decisions. You have opinions on LLM and agent architecture, not just executing someone else's roadmap. You're structured in managing deliverables across engineering and data science, surface ambiguities early, and drive down production incidents with a culture of efficient response.
Does this sound like the right opportunity to explore?... Let's connect!
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What We Offer
The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels and the base salary can vary based on your assessed level. Compensation also includes meaningful equity, healthcare, unlimited PTO, and more.
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Remote - US
Working pattern and location restrictions need checking in the full posting.
Equal Employment Opportunity at Machinify We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/