Every business is under pressure to do more with AI. Axial Search helps define, assess and recruit the leaders who turn that ambition into lasting value. From the executives who own your AI agenda to the technical teams who build it, we recruit the people to deliver your AI transformation.

Whether you're thinking about a permanent AI executive search, hiring a fractional AI leader, or seeking tactical AI recruitment services, our networks have been curated to include AI professionals with the skills to move your organization forwards.

There is no shortage of technically brilliant candidates. Knowing which of them can lead and deliver change is another thing entirely — and it's the difference between transformation and an expensive false start.

Those leaders are rare. Finding them is what Axial Search exists to do. Get in touch to learn more: info@axialsearch.com

Axial Search

Axial Search is a specialist executive search firm built for one kind of hire: leaders who help organizations navigate AI transformation. Apply today to express your interest in roles like this one.

Visit our website to learn more about our process and explore free tools for your job search, including our live job market dashboard with salary, skills and hiring trend data from thousands of AI transformation roles.

What The Market Looks Like

We've tracked 34,500+ mid-level AI/ML engineering postings in the US over the last six months, with strong demand concentrated in Technology, Professional Services, and Financial Services—and particularly in California, New York, and Texas. Compensation for this cohort typically ranges from $160,000 to $350,000, with a median near $180,000. The strongest candidates bring hands-on experience shipping production ML systems, a track record of collaborating effectively across research and engineering teams, and the ability to balance technical depth with business impact.

Job Responsibilities

Design, develop, and deploy machine learning models and systems that solve real business problems, from ideation through production and monitoringBuild and optimize data pipelines, feature engineering infrastructure, and model training workflows to support model development at scalePartner with data scientists, product managers, and infrastructure teams to understand requirements, scope technical feasibility, and integrate ML systems into production applicationsOwn model performance, debugging, and iteration cycles—diagnosing failures, running experiments, and refining approaches based on production metricsLead code reviews, document technical decisions, and establish engineering practices that make ML systems maintainable and reproducibleDrive adoption of ML tooling, frameworks, and best practices within the team—including MLOps infrastructure, versioning, and deployment automationContribute to technical architecture and strategy discussions around scalability, latency, and resource constraints as ML workloads grow

Candidate Requirements

5–8 years of production ML engineering experience—ship and maintain real models in live systems, not research or prototyping aloneStrong proficiency in Python and common ML frameworks (PyTorch, TensorFlow, scikit-learn); experience with data processing tools and SQLDemonstrated ability to move fluidly between model development and software engineering—comfortable with testing, version control, and deployment pipelinesExperience building and scaling data pipelines, feature stores, or model serving infrastructure; familiarity with MLOps practices and toolingProven track record working cross-functionally—collaborating effectively with data scientists, engineers, and product stakeholders to ship models that drive business valueStrong communication skills; ability to explain technical decisions and tradeoffs clearly to both technical and non-technical audiences

Lead AI Engineer

What the job involves