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About This Role
Are you ready to be part of a company that's not just talking about the future, but actively shaping it? Join The AES Corporation, the largest US-based global power company with a team of 8,300 employees across 12 countries.
AES has been ranked #1 by BloombergNEF in renewable energy sales to corporations in the US and Americas for five consecutive years, providing electricity for millions of people worldwide.
We are proud to foster a strong workplace culture, earning prominent positions in Great Place to Work™ rankings across the markets where we operate. AES was also named one of the World’s Most Ethical Companies for the 13th consecutive year in 2026, highlighting our dedication to integrity, transparency, and responsible business practices.
Our spirit of innovation continues to earn industry recognition. AES is the only seven-time winner of the Edison Electric Institute’s Edison Awards in the twenty-first century, a distinction honoring global leadership in advancing the electric power industry.
If you're ready to be part of a company that's not just adapting to change, but driving it, AES is the place for you. We're not just building a more sustainable future, we're powering it. Apply now and energize your career with a true leader in global energy.
Embark on an exciting journey with AES as we pioneer the future of energy through Maximo, our innovative growth venture. Maximo, propelled by an AI-enabled robot, is transforming the construction of solar projects by expediting their completion. As a pivotal contributor to our mission of scaling solar energy production at an unparalleled pace, Maximo is leading the charge to meet the urgent global demand for net-zero emissions. Maximo team members are firm believers that accelerating decarbonization necessitates audacious actions, empowering the world to fulfill future needs.
Job Description
We are seeking a highly skilled and experienced Senior Robotics Perception and AI Engineer to join our team. In this role, you will be responsible for developing, optimizing and implementing cutting-edge perception and AI algorithms to enable our robots to understand and interact with the world around them. You will leverage your deep expertise in computer vision, machine learning, and robotics to drive innovation and solve complex challenges. Duties will include developing advanced perception algorithms for tasks such as object detection, segmentation, and pose estimation, as well as leading the technical roadmap for the perception part aligned with our vision and Product Roadmap.
A successful candidate is strongly motivated and passionate about solving perception and AI/ML problems and pushing the boundaries of what is possible today and will be an entrepreneurial, mission-driven individual responsible for actively progressing, developing, and executing the technical roadmap of our solar module installation robotic system. This individual will take on the responsibility of defining, designing, and implementing the perception software stack architecture and guide the Robotics and Hardware engineers to identify the best sensor suite. In addition, this person will take the ownership of developing and maintaining machine learning pipeline, deploying new models to production, and monitoring their performance collaborating closely with the engineer team to ensure seamless integration of machine learning models and perception algorithm into our applications.
As a specialist in the Maximo business, this position will work collaboratively across the Maximo, external industry partners across the value chain, and AES teams, including engineering, business development, construction, finance, supply chain, and strategy.
Major Responsibilities
- Develop and implement advanced high-performing perception algorithms for real-time tasks such as object detection, segmentation, and pose estimation based on variety of sensor data (Lidar, Camera, etc)
- Design, train, optimize, deploy and maintain AI/ML models for robust and accurate perception in challenging environments.
- Enhance our machine learning pipeline and related tools to support development, experimentation, continuous integration, continuous delivery, verification/validation, and monitoring of AI/ML models in the field.
- Integrate perception systems with robotic platforms to enable autonomous manipulation, navigation, and human-robot interaction.
- Analyze and process sensor data (e.g., camera, lidar, radar, etc.) to extract meaningful information.
- Translate product level requirements into technical design criteria.
- Work with engineers (robotics, hardware, etc.) and product team to define hardware/software architecture and technical roadmap
- Collaborate with cross-functional teams, including hardware engineers, software engineers, and control engineers, to ensure seamless integration of perception systems.
- Stay up to date with the latest advancements in computer vision, machine learning, and robotics to drive innovation and improve product performance.
- Provide technical leadership and mentorship to junior engineers, fostering a culture of innovation and continuous learning.
Requirements
- Master's or PhD in Computer Science, Robotics, or a related field.
- 5+ years of experience in computer vision, machine learning, and/or robotics.
- Strong theoretical foundation in computer vision, image processing, and machine learning algorithms.
- Proficiency in programming languages such as Python, C++, and ROS2.
- Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
- Experience with real-time systems and embedded platforms.
- Knowledge of robotics platforms and sensor systems.
- Founder’s mentality: Entrepreneurial passion for getting things done and a “make it happen” attitude with an intellectual curiosity to seek new opportunities.
- Skill and Behavior: Capability to work dynamically and collaboratively across multiple teams in a fast-paced and technical business environment with minimal supervision. Excellent communication skills. Results-oriented, “can-do” attitude, and “get things done” mentality; comfortable with uncertainty and ambiguity; no compromise on attention to quality and details.
- Technology fluency: Demonstrated ability to understand solar engineering and technology concepts, question assumptions, and make informed product and technology decisions. Technical understanding of automation, robotics, computer vision, machine learning and/or artificial intelligence, is a plus.
Travel: 30% travel
AES is an Equal Opportunity Employer who is committed to building strength and delivering long-term sustainability through diversity and inclusion. Respecting all backgrounds, differences and perspectives enables us to improve the lives of our people, customers, suppliers, contractors, and the communities in which we live and work. All qualified applicants will receive consideration for employment without regard to sex, sexual orientation, gender, gender identity and/or expression, race, national origin, ethnicity, age, religion, marital status, physical or mental disability, pregnancy, childbirth, or related medical condition, military or veteran status, or any other characteristic protected under applicable law. E-Verify Notice: AES will provide the Social Security Administration (SSA) and if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization. The expected salary for this position, at commencement of employment, is between $145,000 and $181,050/year; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position also includes annual bonus. The benefits offered for this position are: medical, dental, and vision coverage, life insurance, 401(k) eligibility, and paid time off (including vacation, sick leave time, and parental leave). Details of participation in these benefit plans will be provided if a candidate receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Apply by clicking the application link below and submitting your information. The deadline to apply for this role is
Salary Context
This $145K-$181K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At AES Corporation, 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 $212,040 based on 13,780 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($163K) sits 23% below the category median. Disclosed range: $145K to $181K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
AES Corporation AI Hiring
AES Corporation has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Arlington, VA, US. Compensation range: $181K - $181K.
Location Context
Across all AI roles, 6% (708 positions) offer remote work, while 10,737 require on-site attendance. Top AI hiring metros: New York (3,257 roles, $221,000 median); San Francisco (2,766 roles, $260,550 median); Los Angeles (1,580 roles, $210,000 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 Safety roles lead at $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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