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LOCATION: Avon / Ohio (US\-OH), United States \| BRAND: Knorr\-Bremse \| REQUISITION ID: 10553 \| JOB GRADE: 19 \| ON\-SITE/REMOTE: On\-site
At Knorr\-Bremse, our mission is to make mobility safer, more efficient, and better for the environment on roads and railways. This shared passion brings us together around the world and motivates us every day. Based in Munich, Knorr\-Bremse Group is the global leader in braking systems and a top supplier of safety\-related sub\-systems for rail and commercial vehicles.
To support our growth and teamwork in North America, Knorr Brake Holding Corporation (KBHC) provides shared services for our truck and rail brands, such as Bendix CVS, Knorr Brake Company, KB Signaling, and New York Air Brake. When you join KBHC, you work with skilled and dedicated colleagues who share your sense of purpose. You will find meaningful opportunities, gain diverse experiences, and help achieve important goals across our North American truck and rail divisions.
Knorr Brake Holding Corporation is proud to be an Equal Employment Opportunity (EEO) employer. We are committed to providing equal opportunities to all qualified applicants, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disability status, or genetic information.
JOB DESCRIPTION:
Position Summary:
This position is a dynamic and results\-oriented Director of AI \& Digital Transformation to lead our digital initiatives across the organization. This role is pivotal in shaping our future by identifying and implementing cutting\-edge digital solutions, particularly in AI, that will enhance our products, services, and operations. The ideal candidate will be a strategic thinker with a proven track record of driving significant digital change and delivering measurable business results.
Essential Functions:
Strategy \& Vision* Develop and execute a comprehensive digital transformation strategy with strong emphasis on AI.
- Identify new business opportunities and models enabled by digital technologies.
- Champion a culture of innovation and continuous improvement across the enterprise.
Leadership \& Execution
- Lead and mentor a cross\-functional team of digital experts, data scientists, and engineers.
- Oversee the entire lifecycle of digital and AI projects, from conception to deployment and scaling.
- Collaborate with senior leadership to align digital initiatives with overall company objectives.
Impact \& Value Creation
- Define and track key performance indicators (KPIs) to measure the impact and ROI of digital initiatives.
- Drive the adoption of AI\-powered solutions to optimize processes, enhance decision\-making, and create new revenue streams.
- Ensure all digital initiatives are compliant with relevant regulations.
Stakeholder Management
- Build strong relationships with internal and external stakeholders to foster collaboration and drive adoption.
- Communicate the vision, progress, and impact of the digital transformation strategy across the organization, including executive leadership.
Knowledge
- Strong expertise in AI, machine learning, data analytics, and emerging digital technologies, and how to apply them to business challenges
- Proven understanding of digital transformation strategy and execution at an enterprise level, including identifying new business opportunities
- Strong business acumen with the ability to translate technical solutions into measurable business value (ROI, efficiency, revenue growth)
- Experience leading large\-scale digital programs and managing cross\-functional teams in a matrix environment
- Strong stakeholder management and communication skills, including working with senior leadership
- Knowledge of change management and driving adoption of new digital and AI solutions
- Awareness of governance, compliance, and industry trends related to digital technologies
Skills
- Deep understanding of AI, machine learning, data analytics, and other emerging digital technologies.
- Strong business acumen and the ability to translate technical concepts into tangible business value.
- Excellent leadership, communication, and interpersonal skills, with the ability to influence cross\-functional teams.
- Strategic thinker with the ability to manage ambiguity and drive results.
Experience
- A minimum of 10 years of experience in IT/Digital roles, with at least 5 years in a leadership position overseeing digital transformation or AI projects.
- Proven experience in developing and implementing AI strategies that have delivered significant business value.
- Experience in managing and mentoring teams.
- Experience in the manufacturing or transportation industry is a plus.
Education
- Bachelor’s degree in Computer science, Engineering, Business, or a related field.
- Master’s degree is preferred.
Position Requirements:
The demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.
The anticipated salary range for candidates who will work in Avon, OH is $142,900–$238,100 per year. The final pay offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and years of experience within the job, the type of years and experience within the industry and education. KBHC is a multi\-state employer, and this pay scale may not reflect positions that work in other states or locations. Provided they meet all eligibility requirements under the applicable plan documents, employees (and their eligible dependents) will be eligible to enroll in group healthcare plans that offer medical, dental, vision, and basic life and disability insurance. Employees also will be able to enroll in our company’s 401k plan. Employees will also receive 120 hours of vacation leave and 40 hours of Personal Paid Absence every year. Employees will also enjoy 12 paid holidays, and 1 floating holiday throughout the calendar year, subject to relevant terms outlined in the employee handbook. 6 weeks of paid parental leave will also be available for use. Requirements for these benefits will be controlled by applicable plan documents and policies. Employees working on federal contracts covered by the Federal Paid Sick Leave requirements will be notified and will receive benefits consistent and compliant with the FPSL requirements. Hired applicant will be able to purchase company stock, subject to the relevant plan documents and annual bonuses based on achievement of certain metrics of up to 10% of annual salary. This is intended to provide a general description of benefits and other compensation and is not a substitute for applicable plan documents or company policies. Applications for this position are accepted on an ongoing basis.
*Please note: At this time, we are not able to offer immigration sponsorship for new hires. All applicants must be currently authorized to work in the United States on a full\-time basis without the need for current or future employment\-based visa sponsorship.*
*\#LI\-AT1*
*\#LI\-Hybrid*
Become part of our team!
Join us in shaping the mobility of the future!
We \- that's around 30,000 employees worldwide. At over 100 locations in more than 30 countries, we are committed to progress on rail and road through technological excellence, sustainable management and social responsibility. Our most recent turnover was 7\.8 billion euros. With us, you can expect an exciting and varied job in an international environment as well as an attractive package.
Salary Context
This $142K-$238K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Knorr-Bremse, 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 $181,170 based on 12,692 positions with disclosed compensation. Director-level AI roles across all categories have a median of $247,800. This role's midpoint ($190K) sits 5% above the category median. Disclosed range: $142K to $238K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Knorr-Bremse AI Hiring
Knorr-Bremse has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Avon, OH, US. Compensation range: $238K - $238K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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