Interested in this AI/ML Engineer role at Siemens?
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Pioneering in America, from the first mile to the last. This is what drives us!
For more than 160 years, Siemens has been an integral provider of infrastructure, electrification, and transportation solutions in the United States. Automation’s impact on the railway industry is second only to the effects of digitalization. Combine them and the results are transformative! We work at the leading edge of this movement, applying our proven expertise in digitalization to rail infrastructure and automation.
Our innovative solutions deliver greater safety, punctuality, reliability, and sustainability across the line, all while reducing costs for mass transit and freight transportation systems. We are continuously developing new answers for rail automation – often to questions that haven’t been asked yet.
*We’re proud to be Great Place to Work® certified—a reflection of our commitment to creating an environment where innovation thrives and every voice matters. Apply today and be part of shaping the future with us!*
Position Overview:
The Doors Engineering Design Lead will report to the Doors Engineering Manager in Sacramento, CA, joining a team of Doors / Steps / Lifts Systems Engineers and Design Engineers for coaches and light rail. You will coordinate with system engineers for design requirements and lead the design efforts, which will include both doing design and coordinating/leading other designers. You will be involved in bid phase, design phase, customer presentations, solving production and field issues, design optimization (DFC, DFM, DFA, DFS) and continuous improvement. There are many different systems (typically mechatronic) within the Doors / Steps / Lifts group and you be involved with all of them throughout their lifecycle.
What Your Day\-to\-Day Will Look Like:
Leading Design Effort
- Review technical specifications and industry standards.
- Coordinate with system engineers and suppliers for requirements and design interfaces.
- Lead door design engineers and collaborate with other engineering groups.
- Conduct design work in Creo, including structural analysis and bolted joint calculations.
- Participate in design reviews, prototype testing, and produce/review supplier specifications.
Design Optimization \& Hands On Experience
- Optimize designs for manufacturing, assembly, cost, standardization, performance and serviceability
- Work on standardizing parts and hardware used in designs
- Spend time on shop floor to fully understand install process to inform DFA improvements
- Spend time on the car, in testing and in the field to make sure your knowledge of the design/system includes hands on experience.
- Troubleshoot design issues on the car and be able to make the necessary adjustments to better inform design for serviceability and performance improvements
- Work with and get feedback from production, industrial engineering, production engineering, and the test / commission group
System Integration \& Interface Design
- Ensure proper system integration into the vehicle
- Work with other mechanical and electrical engineering groups for coordinated interfaces
- Given the nature of moving systems, doing thorough interference checks across the whole range of movement, that take into account tolerances is critical
- Design sufficient adjustments into the systems while maintaining proper bolted joint design
- Help to determine carshell interfaces and optimal datums
Mentorship
- Provide technical mentorship to doors design engineers
Travel:
- Some domestic and international travel. Travel multiple times a year is typical
To Thrive in This Role, You'll Have:
- BS in Mechanical Engineering or related technical field \+ 8 years of experience or a MS in Mechanical Engineering or related technical field \+ 5 years of experience
- Solid design engineering experience
- Full project lifecycle experience (engineering, procurement, manufacturing, testing, warranty)
- Must be legally authorized to work in the United States without sponsorship
What Will Make You Stand Out:
- In depth knowledge of design best practices, GD\&T, Creo, bolted joints, mechanisms, etc.
- Hands on experience with troubleshooting and adjusting mechatronic systems
- Design leadership experience
- EIT/FE Certificate or PE license
- Experience with mechatronic systems and how to read electrical schematics
- MS degree in Mechanical Engineering
- Rolling stock engineering experience with rail vehicle platforms
- Working knowledge of railway design standards: AAR Section M, APTA, ASME, PRIIA, and other rail specifications
- Experience with LRV and coach systems
Candidates should be willing to work in non\-climate\-controlled environments and inclement weather if required or if applicable.
Why you'll love working for Siemens!
- Freedom and healthy work\-life balance– Health, Dental, Vision Insurance, HSA/FSA, Commuter Benefits – starting Day 1!
- We believe that each member of our team is accountable for making decisions, solving problems, and taking actions that contribute to long\-term impact and financial success.
- We do the right thing. We stand for green innovations and meaningful solutions with impact on customers, ecosystem partners, society, and environment.
- We are frontrunners in digitalization and building platforms. Therefore, we are hiring ambitious forward\-thinkers who want to have a real impact.
- Solve the world's most significant problems – Be part of exciting and innovative projects.
- Opportunities to contribute your innovative ideas and get paid for them! Take advantage of our Tuition Reimbursement program, Mentor Programs, and your development through online learning. We operate daily with a growth mindset \- that's why Siemens consistently ranks on the Fortune World's Most Admired Companies list!
- Employee perks and discounts in addition to our 401k match and generous Paid Time Off
Siemens offers a variety of health and wellness benefits to employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html.
The base salary range for this position in California is $120,000\- $145,000. The salary may be higher or lower depending on the budget and the candidate's experience, knowledge, skills, and qualifications.
Join the growing team at our world\-class train manufacturing facility in Sacramento, CA. Siemens Mobility, Rolling Stock Division is the North American market leader in the production of passenger locomotives and coaches, and light rail vehicles.
\#LI\-EB1
$120,000\.00 $145,000\.00
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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Siemens, 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 $166,983 based on 13,781 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Siemens AI Hiring
Siemens has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Alpharetta, GA, US, Lebanon, OH, US, Wendell, NC, US. Compensation range: $75K - $188K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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