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Job Title: Senior Counsel, AI Law
At Siemens, we're not just building technology; we're building the future. Our innovations power industries, transform infrastructure, and redefine the way we live and work. As a global leader in electrification, automation, and digitalization, we are at the forefront of employing artificial intelligence (AI) to drive unprecedented advancements across our diverse portfolio with a strong focus on industrial AI.
Siemens Foundational Technologies (FT) is our central, global Research \& Development home for Data \& Artificial Intelligence (DAI) and leads the transition to operating as "ONE Tech Company," Siemens' strategic vision to harmonize its diverse, world\-class business units into a highly integrated technology ecosystem.
Transform the everyday with us!
Position Overview:
The rapid evolution of AI presents both immense opportunities and complex legal challenges. As Senior Counsel specializing in AI Law, you will be a critical advisor, guiding our product development, business strategies, and research initiatives through this dynamic landscape and helping to shape our Industrial AI offerings. You will play a pivotal role in ensuring that Siemens' AI innovations are not only technologically superior but also legally sound, ethically responsible, and compliant with emerging global regulations.
You will make an impact by:
- Providing practical legal guidance on AI, data, and emerging technology matters.
- Advising on evolving AI regulations, governance frameworks, and industry standards.
- Supporting data acquisition, licensing, privacy, security, and governance strategies critical to AI development and deployment.
- Counseling on intellectual property, technology licensing, innovation, and R\&D initiatives.
- Partnering with product and engineering teams to embed legal and compliance considerations throughout the technology development lifecycle.
- Identifying and mitigating legal and business risks associated with AI and advanced technologies.
- Drafting, reviewing, and negotiating complex technology, commercial, and partnership agreements.
- Collaborating cross\-functionally to enable responsible innovation while supporting business growth objectives.
- Advising on legal and regulatory risks associated with AI and emerging technologies, helping the business navigate evolving requirements while enabling innovation.
- Drafting, reviewing, and negotiating complex technology, commercial, licensing, and partnership agreements.
- Collaborating closely with engineering, product, R\&D, data science, cybersecurity, and business teams to integrate legal guidance throughout the development and deployment of AI solutions.
- Monitoring developments in AI legislation, regulation, and industry standards, providing strategic counsel on emerging legal trends and policy considerations.
- Promoting AI compliance and responsible innovation through partner training, guidance, and best\-practice education across the organization.
Interested? We are looking for a colleague to join our international team where your legal expertise will directly shape the ethical, compliant, and groundbreaking deployment of AI solutions on a global scale.
You will impress us by having these qualifications:
Juris Doctor (JD) degree from an accredited law school and active membership in good standing with a US State Bar.
Minimum 7 years of relevant legal experience as in\-house counsel or at a top law firm, with a significant focus on technology law.
3\+ years of experience advising on AI technologies and related legal issues. This experience should ideally include time spent at a multinational company with a focus on AI where you advised on the development and deployment of AI solutions.
5\+ years of experience in legal support for development of software or based products in cloud, software, or hardware sectors with substantial AI offerings including all related topics e.g. regulatory requirements, IP or tax
7\+ years of experience supporting management and business clients with advice and practical solutions
Strong understanding of data privacy laws (e.g., CCPA, GDPR) and their intersection with AI.
Familiarity with intellectual property concepts related to software, data, and AI.
Preferred Qualifications:
Excellent analytical, communication, problem solving and interpersonal skills, with the ability to translate complex legal concepts into clear, actionable advice for technical and business teams.
A proactive, solution\-oriented approach with the ability to thrive in a fast\-paced, innovative, and rapidly evolving environment.
Ability to manage multiple worldwide projects simultaneously and work effectively both independently and as part of a team.
People skills to collaborate effectively with diverse stakeholders both in the U.S. and globally, bridging varying perspectives and experiences.
Experience with open\-source AI models and their legal implications.
Background in software engineering, data science, or related technical fields.
Experience in a regulated industry (e.g., healthcare, industrial automation, finance) where AI is being applied.
You'll Benefit From
Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here. The pay range for this position is $191,000\-$328,000 annually with a 25% annual target incentive of the base salary. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and premium geographic location.
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.
Salary Context
This $191K-$328K range is above the 75th percentile 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 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($259K) sits 19% above the category median. Disclosed range: $191K to $328K.
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.
Siemens AI Hiring
Siemens has 4 open AI roles right now. They're hiring across AI/ML Engineer, Research Scientist. Positions span New York, NY, US, Santa Clara, CA, US, Seattle, WA, US. Compensation range: $158K - $341K.
Location Context
AI roles in Seattle pay a median of $236,900 across 267 tracked positions. That's 9% above the national 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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