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Job Description:
About the Role
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Artificial Intelligence is evolving at an unprecedented pace, creating new opportunities, business models, and competitive dynamics across industries. Schneider Electric is seeking an AI Innovation Strategist to help the company stay ahead of these shifts by identifying, assessing, and interpreting emerging AI technologies before they become mainstream.
As a senior individual contributor within the Strategy \& Innovation organization, you will act as an early signal detector for the business, translating developments across the AI ecosystem into actionable strategic insights. You will engage with cutting\-edge research, startups, technical communities, and industry experts to understand where AI is headed, what technologies matter most, and how emerging innovations could impact Schneider Electric.
This role is ideal for a technically credible AI practitioner who combines deep hands\-on expertise with intellectual curiosity, strong external networks, and the ability to connect technology trends to business strategy. Your impact will come through the quality of your insights, the strength of your network, your technical judgment, and your ability to influence strategic thinking across the organization.Role Responsibilities
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### Detect Emerging Trends and Weak Signals
- Track AI models, tools, paradigms, startups and research directions.
- Engage through conferences, workshops, technical communities and informal networks.
- Distinguish genuine shifts from hype.
### Build and Leverage External Networks
- Develop relationships across AI labs, startups, open\-source communities and industry experts.
- Gather insights beyond public announcements.
- Represent Schneider Electric in the broader AI ecosystem.
### Evaluate Technologies and Startups
- Rapidly assess new technologies, products and startup claims through hands\-on experimentation.
- Produce clear opinions on what works, what does not, and why.
### Inform Strategy and Competitive Intelligence
- Work closely with Strategy \& Innovation leaders to develop positions on emerging AI topics.
- Analyze competitor announcements and implications for Schneider Electric.
### Accelerate Organizational Learning
- Share insights through concise briefings, demos and strategic memos.
- Maintain a living view of technologies to watch, evaluate, adopt or avoid.
(External) English Qualifications:
Qualifications
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### Technical Background
- Master's degree or higher in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Typically 5\+ years of technical experience in AI, ideally as a Research Engineer, Applied Scientist, ML Engineer, or similar role in an AI startup, technology company, or research lab.
- Strong hands\-on experience with modern AI technologies and ecosystems; ability to rapidly prototype, test and compare emerging approaches.
- Ability to understand research literature and engage credibly with technical experts.
- Technical depth sufficient to independently validate claims and challenge vendors.
- Existing involvement in the AI ecosystem through conferences, open\-source communities, research collaborations or professional networks.
### Mindset and Communication Skills
- Deep curiosity about technology and its strategic implications.
- Strong external orientation and network\-building capabilities.
- Strong oral and written communication skills.
- Capacity for strategic analysis and synthesis, translating complex topics into meaningful recommendations.
- Independent judgment and ability to form evidence\-based opinions.
- Comfortable operating with ambiguity and incomplete information.
Seniority
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- Senior individual contributor.
- Impact comes from technical credibility, quality of insights, strength of network and strategic influence.
Local Benefits (English):
At Schneider, we believe that every employee is a talent who deserves equal opportunities. This means you matter. Every individual needs to feel valued, supported, and treated fairly to do their best work.
Our Total Rewards is our way of saying: “We see you. We value you”. It’s more than just pay and benefits\- it’s a meaningful investment in you. It is designed for you to perform, grow, feel safe, and elevate your potential to shine as an impact maker.
For this U.S. based position, the expected pay range is USD 117,600 \- USD 176,400 per year. This pay range includes base pay and short\-term incentives. The compensation range for this full\-time position applies to candidates located within the United States. Our pay ranges are determined by reviewing roles of similar responsibility and level. Within the pay range, individual pay is determined by several factors including performance, knowledge, job\-related skills, experience, and relevant education or training.
Schneider Electric is there when it matters most to you
Our Total Rewards package outlines all the benefits and support you’ll enjoy as part of the Schneider Electric team:
Care for Yourself and Your Family. We ensure you feel secure with benefits that help you and your family thrive: medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks, flexible work arrangements, paid family leaves, well\-being programs, 12 holidays per year, and 15 days of paid time off per year.
Invest and Plan Your Future. We help you plan and invest for the future with competitive pay and programs including base salary, incentives, company share ownership, and 401(k) with match.
Grow Your Skills and Career. We support development through performance discussions, global opportunities, the Schneider Career Hub, and learning platforms like Coursera.
Team Up in the Workplace. We encourage collaboration, recognition, sharing your voice, and an inclusive workplace.
Support Your Community. We make a difference through volunteer leave, programs with the Schneider Electric Foundation, youth education initiatives, and military leave benefits.
(External) English Company Boiler Plate: Looking to make an IMPACT with your career?
When you are thinking about joining a new team, culture matters. At Schneider Electric, our values and behaviors are the foundation for creating a great culture to support business success. We believe that our IMPACT values – Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork – starts with us.
IMPACT is also your invitation to join Schneider Electric where you can contribute to turning sustainability ambition into actions, no matter what role you play. It is a call to connect your career with the ambition of achieving a more resilient, efficient, and sustainable world.
We are looking for IMPACT Makers; exceptional people who turn sustainability ambitions into actions at the intersection of automation, electrification, and digitization. We celebrate IMPACT Makers and believe everyone has the potential to be one.
Become an IMPACT Maker with Schneider Electric – apply today!
€40 billion global revenue
\+9% organic growth
150 000\+ employees in 100\+ countries
You must submit an online application to be considered for any position with us. This position will be posted until filled. *Schneider Electric aspires to be the most inclusive and caring company in the world, by providing equitable opportunities to everyone, everywhere, and ensuring all employees feel uniquely valued and safe to contribute their best. We mirror the diversity of the communities in which we operate, and ‘inclusion’ is one of our core values. We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do.*
*At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value. Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders. You can find out more about our Trust Charter* *here*
*Schneider Electric is an Equal Opportunity Employer. It is our policy to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color, gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status, or any other legally protected characteristic or conduct.*
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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Schneider Electric, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Schneider Electric AI Hiring
Schneider Electric has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Andover, MA, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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