Interested in this AI/ML Engineer role at Life Fitness / Hammer Strength?
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Join us as we empower the world to work out, creating healthier lives together.
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At Life Fitness / Hammer Strength, we inspire the world to work out. We are a high\-performing team focused on using AI, data, and technology to improve how we operate, build products, and serve customers around the world.
We are looking for a Leader of Artificial Intelligence to lead the development and deployment of AI solutions across operations, supply chain, commercial, and product functions. This role combines technical leadership, business partnership, and team development to deliver scalable solutions with measurable business impact.HOW YOU'LL MAKE AN IMPACT (RESPONSIBILITIES):Lead AI Solutions That Drive Results* Lead AI initiatives from concept through deployment and adoption
- Translate business challenges into scalable machine learning, optimization, and generative AI solutions
- Deliver use cases including:
+ Predictive maintenance and reliability analytics
+ Demand forecasting and inventory optimization
+ Production scheduling and operational efficiency
+ Quality and warranty analytics
+ Sales forecasting and margin insights
- Embed solutions into business workflows to improve decision\-making and performance
Partner Across the Business* Collaborate with Operations, Supply Chain, Commercial, Product, Engineering, Finance, and IT teams to identify and prioritize AI opportunities
- Communicate technical insights in clear, business\-focused language
- Support measurable outcomes including efficiency gains, cost savings, and revenue impact
Advance Product \& Digital Innovation* Partner with Product Management and Software Engineering teams to support AI\-enabled capabilities within connected products and digital platforms
- Contribute to customer\-facing and internal AI applications that enhance training, performance, and user experience
- Support scalable, secure, and reliable model deployment practices
Lead \& Develop Talent* Lead and develop a small team of data scientists and machine learning engineers
- Promote best practices in model development, governance, and MLOps
- Help strengthen AI literacy and adoption across the organization
WHAT YOU BRING TO THE TEAM (QUALIFICATIONS):* 6 to 10\+ years of experience in AI, machine learning, analytics, or data science
- Experience developing and deploying models in production environments
- Strong understanding of machine learning, predictive analytics, optimization, and generative AI
- Experience supporting manufacturing, operations, supply chain, or product organizations preferred
- Experience in B2B, industrial, or performance\-driven environments strongly preferred
- Familiarity with cloud platforms, enterprise systems, and modern analytics toolchains
- Strong problem\-solving, communication, and cross\-functional collaboration skills
- Ability to operate with ownership, urgency, and continuous improvement mindset in a matrixed environment
WHY LIFE FITNESS / HAMMER STRENGTH* Help shape how AI transforms a global fitness and performance brand
- Work on high\-impact operational, commercial, and product challenges
- Collaborate with teams that value innovation, accountability, and execution
- Be part of a culture built around performance, teamwork, and inspiring healthier lives
*If you are passionate about applying AI to solve complex business problems and building solutions that create measurable impact at scale, we would love to talk with you.*
At Life Fitness / Hammer Strength, we think customer first, play as one team, and raise the bar on fitness innovation—in the gym and in every corner of our facilities. We persevere and get it done, with a clear purpose to inspire each other to live healthier lives. If you’re ready to bring out the best in people while powering the future of fitness manufacturing, we invite you to apply.
Want to take the next step in your career?Life Fitness / Hammer Strength takes pride in our talented employees and believes in providing opportunities for further growth and advancement. We encourage you to test your strengths, push your limits, and unleash your potential. If you feel the position is right for you, we invite you to apply. We’ll work with you closely to support you throughout the hiring process. If your CV/ resume shows that your skills and experience have synergy with the job description, then we’ll hop on a call to get to know you and your experience and discuss the position in more detail. If it’s not the right opportunity this time, we’ll always let you know.
At Life Fitness / Hammer Strength, we believe in taking care of our team with a comprehensive total rewards package that includes competitive pay and a range of valuable benefits. The salary range for this position, intended for U.S. applicants, is $149,400 \- $182,500 annually.The actual salary will vary based on applicant’s education, experience, skills, and abilities. The salary range reflected is based on a primary work location of Rosemont, IL and the actual salary may vary for applicants in a different geographic location.This position is eligible to participate in Life Fitness / Hammer Strength’s annual Manager Incentive Plan to receive an annual discretionary bonus in addition to base salary. The amount of bonus varies based on company and individual performance goals and is subject to the terms and conditions of the applicable incentive plan.
Life Fitness / Hammer Strength offers a comprehensive package of benefits for full\-time team members, including, but not limited to: a 401(k) savings plan with 4% employer match; medical, dental and vision insurance, parental, medical and military leaves of absence, paid time off, including 12 paid holidays throughout the calendar year, paid vacation days beginning at 13 days annually, paid sick leave as provided under state and local paid sick leave laws, company paid short\-term disability and optional long\-term disability, health savings account, health care and dependent care reimbursement accounts, employee and dependent life insurance and supplemental life and AD\&D insurance, hospital indemnity; identity protection, legal services, adoption assistance, tuition assistance, commuter benefits, employee discounts, and an employee assistance program that includes free counseling sessions. Eligibility for benefits is governed by the applicable plan documents and policies.
Life Fitness / Hammer Strength is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. Life Fitness / Hammer Strength complies with all applicable federal, state, and local laws regarding employment*,* recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state, or local laws.
There continues to be a significant increase in phishing attempts across all industries where fraudsters are impersonating real employees and sending fictitious job offers to applicants in a scheme to obtain sensitive information. Please note that Life Fitness/Hammer Strength will never ask for your financial information at any part of the interview process, including the post\-offer stage, and will only correspond through “@lifefitness.com” or "@indoorcycling.com" domain email addresses or “[email protected]” for U.S. opportunities.
Life Fitness/Hammer Strength does not accept applications, inquiries or solicitations from unapproved staffing agencies or vendors.
Salary Context
This $149K-$182K range is below 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 Life Fitness / Hammer Strength, 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 in Demand for This Role
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. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($165K) sits 24% below the category median. Disclosed range: $149K to $182K.
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.
Life Fitness / Hammer Strength AI Hiring
Life Fitness / Hammer Strength has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Rosemont, IL, US. Compensation range: $182K - $182K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
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
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