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About This Role
Head of Transportation \& Supply Chain Manager
Here at Siemens, we take pride in enabling sustainable progress through technology. We do this through empowering customers by combining the real and digital worlds, thereby improving how we live, work, and move today and for the next generation! We know that the only way a business thrives is if our people are thriving. That’s why we always put our people first. Our global, diverse team would be happy to support you and challenge you to grow in new ways. Who knows where our shared journey will take you?
Transform the everyday with us!
Siemens Industry is looking for a Head of Transportation \& Supply Chain Management for our SI Logistics organization. The position will be based in Alpharetta, GA, and must have the ability to support other regional locations. The Regional Head of Transportation \& Supply Chain Management will be an integral member of a diverse and dynamic team that offers you the chance to grow, contribute and learn as far as your growth mindset takes you.
We are seeking a Head of Transportation \& Supply Chain Manager for a hybrid position, allowing you the flexibility to work both on\-site and remotely each week.
The Head of Transportation \& Supply Chain Manager will oversee our sourcing and operation teams for the End‑to‑End planning, coordination, and execution of freight, including standard and over\-dimensional project transportation management. This role is responsible for ensuring safe, compliant, and cost‑effective delivery of critical equipment through close coordination with internal stakeholders, logistics providers, carriers, and regulatory authorities. This person will be responsible for the North America region which includes the following: U.S., Canada, Mexico and part of Central America.
The ideal candidate combines strong project management and process improvement skills with deep knowledge of various modes of transportation (LTL, TL, Air, Sea, and Rail), transportation network design \& optimization, and regulatory compliance across domestic and international freight movements.
Key Responsibilities:
Team Management \& Leadership
- Detail\-Oriented / Strategic Thinker – proven ability to develop creative insights and solutions using operational excellence problem solving tools.
- Facilitator / Team Leader – ability to lead and facilitate meetings and team initiatives and timelines.
- Written \& Oral Communication – ability to digest inputs and re\-craft message to leadership team/upper management, etc.
- Manage \& lead a dynamic team to ensure efficient execution transport management activities.
- Develop your team by ensuring proper training \& development of all team members, coaching, and proper alignment across all business units.
- Proven ability to manage multiple teams, including Sourcing and Operations (Standard \& Project) logistics teams.
- Identify and recommend improvements to supply chain metrics and performance standards using research, analytical skills knowledge and best practices to secure benefits for the system, (e.g., cost savings, new technologies and innovations, operating efficiency).
- Manage/Lead \& Conduct stewardship or supplier/carrier management meetings to review performance and develop corrective action plans.
- Manage standards/specifications for quality, delivery time, and lead\-time for shipments to ensure on\-time arrival of product to customers.
Data Analysis \& Reporting
- Manage / lead \- analyze end\-to\-end supply chain processes including logistics cost, quality, and performance
- Analyze historical trends \& performance data of transportation suppliers to provide input for business decisions.
- Lead your team to analyze performance data to identify business plan variances using established systems and ad\-hoc problem solving.
- Quarterly Performance Reporting \- Collaborate with internal business units/segments on transportation metrics and key drivers, etc.
Stakeholder Value
- Develop understanding of business needs and define actions to ensure requirements are met
- Evaluate and measure performance of external service providers (e.g., distributors, third party logistics providers) using applicable performance metrics to ensure quality, service, efficiency, and delivery to specifications as set forth in agreements.
- Participate in Business Review meetings and cross functional projects across the supply chain network to improve processes and strengthen our supply chain.
Cost, Performance \& Risk Management
- Problem Solving / Analysis \- identify root causes and generate technical solutions to support business decisions.
- Identify and mitigate transportation risks related to scheduling, safety, compliance, and cost related concerns.
- File and monitor damage and shortage claims while leading carriers through root\-cause investigations and corrective action plans.
- Establish and maintain annual and periodic freight forecasting and budgeting assumptions leveraging transportation market intelligence and business demands flows.
- Monitor budgets, track transportation costs, and identify cost‑saving opportunities.
- Resolve delivery issues, delays, or disruptions while maintaining project timelines.
Compliance \& Documentation
- Ensure all team members are properly trained in all government/country requirements and regulation related to transportation documentation, i.e., (letters of credit, permits, customs, insurance, bills of lading, etc.)
- Customs Compliance: Work closely with the USCO team supporting all areas of customs management, i.e. (Customs Entry, Customs Audits and Duty Optimization)
- standards, CTPAT, and EHS requirements.
You’ll win us over by having the following qualifications:
Basic Qualifications:
- Bachelor's Degree
- Computer skills required – Word, Excel, PowerPoint, Project Management
- 15\+ years of experience in transportation team management, well\-versed in domestic \& international transportation management.
- Proven strong organizational, interpersonal, and communication skills, including the ability to articulate complex technological concepts.
- Ability to work effectively in a team environment, working with direct and matrixed resources to ensure customer satisfaction and profitable growth.
- Proven experience managing standard and project transportation deliveries, etc.
- Strong understanding of transportation regulations, permitting, CTPAT, and compliance requirements.
- Experience working with freight forwarders, 3PL, asset\-based transport carriers, etc.
- Excellent communication, coordination, and organizational skills.
- Ability to manage multiple projects concurrently in a fast‑paced environment.
Preferred Qualifications:
- Bachelor's Degree in Supply Chain, Logistics, Engineering, Business, or a related field
- Experience supporting industrial, infrastructure, or power distribution projects.
- Knowledge and familiarity with domestic and international transportation (road, rail, ground, air and ocean freight).
- Strong people management experience and skills.
- Experience working in a large global organization.
- Proficiency in SAP or other ERP systems
- Strong understanding of transportation management tools \& systems, etc.
- Familiarity with Salesforce or other CRM systems
You’ll benefit from:
- Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
About Siemens:
We are a global technology company focused on industry, infrastructure, transport, and healthcare. From more resource\-efficient factories, resilient supply chains, and smarter buildings and grids to sustainable transportation as well as advanced healthcare, we create technology with purpose adding real value for customers. Learn more about Siemens here.
Our Commitment to Equity and Inclusion in our Diverse Global Workforce:
We value your unique identity and perspective. We are fully committed to providing equitable opportunities and building a workplace that reflects the diversity of society, while ensuring that we attract the best talent based on qualifications, skills, and experiences. We welcome you to bring your authentic self and transform the everyday with us.
\#LI\-TA1
$109,670 $188,006 15
Salary Context
This $109K-$188K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 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 Required
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. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($148K) sits 11% below the category median. Disclosed range: $109K to $188K.
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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