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About This Role
Battelle delivers when others can’t. We conduct research and development, manage national laboratories, design and manufacture products and deliver critical services for our clients—whether they are a multi\-national corporation, a small start\-up or a government agency.
We recognize and appreciate the value and contributions of individuals from a wide range of backgrounds and experiences and welcome all qualified individuals to apply.
Job Summary
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We are seeking an early career Robotics AI Engineer to support fast\-moving, IRAD\-style projects at the intersection of artificial intelligence and robotic systems. This is a hybrid position located at our Columbus, OH headquarters.
You will apply AI, machine learning, computer vision, and autonomy algorithms to build robots, sensors, and advanced scientific instrumentation operating in complex environments across chemistry, biology, materials science, and cyber domains. This is a hands\-on role working directly with physical hardware, developing solutions that perform in real\-world conditions.
You will design and integrate AI\-driven capabilities such as perception, navigation, sensor fusion, and autonomous decision\-making, contributing to programs including Battelle’s DART system and PathPlan software. Over time, you will grow into ownership of end\-to\-end pipelines from sensor input to autonomous action.
Responsibilities
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- Develop and integrate AI/ML models on robotic platforms (ground, aerial, maritime) for perception, navigation, and decision\-making
- Integrate, calibrate, and troubleshoot sensors (cameras, LiDAR, IMUs, GPS, depth sensors) to support localization and mapping
- Apply sensor fusion and state estimation techniques to improve system reliability in dynamic environments
- Write production\-quality code in Python and/or C\+\+ within ROS/ROS2 and Linux environments, leveraging modern development tools
- Build and validate perception and autonomy pipelines in simulation and deploy to physical hardware through testing and iteration
- Deploy and optimize AI models on edge computing platforms for real\-time inference
- Conduct field testing and resolve hardware\-software integration issues under real\-world conditions
- Contribute to rapid prototyping efforts supporting IRAD and mission\-driven timelines
- Collaborate with multidisciplinary teams to translate ambiguous requirements into working solutions
- Document designs, testing, and integration processes to support reproducibility
- Support research proposals and present technical findings to stakeholders and external audiences
Key Qualifications
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- Bachelor's degree in Robotics, Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, Mechatronics, or a related technical field.
- 0 to 2 years of experience (including academic projects, internships, research, competitions)
- Proficiency in Python and/or C\+\+ for robotics or autonomous systems
- Hands\-on experience integrating software with physical sensors and hardware
- Foundational knowledge of AI/ML for physical systems (computer vision, planning, control, reinforcement learning)
- Experience with ROS or ROS2
- Familiarity with Linux and version control (Git)
- Strong problem\-solving skills and ability to work in fast\-paced, ambiguous environments
- Must be a U.S. Citizen.
Preferred Qualifications
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- Master’s degree or relevant graduate research in robotics or AI
- Experience with embedded systems, real\-time systems, or hardware\-software co\-design
- Hands\-on work with simulation tools such as Gazebo, NVIDIA Isaac Sim, MuJoCo, or Webots, with experience bridging sim\-to\-real deployment.
- Familiarity with robotics data tools (rosbag, MCAP)
- Hands\-on prototyping skills (3D printing, soldering, wiring, PCB work)
- Experience with AI/ML frameworks (PyTorch, TensorFlow, OpenCV)
- Background in robotics competitions, open\-source contributions, or published research
- Exposure to multi\-agent systems, human\-robot teaming, or swarm robotics
- Familiarity with MATLAB or Simulink
- Interest in autonomy testing, validation, or safe AI systems
- Experience in government, defense, or applied research environments
- Active security clearance or ability to obtain one
Salary Range \& Compensation
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- Battelle is committed to fair and equitable compensation practices. The salary range for this role is $72,000 to $100,000 per year, in addition to our comprehensive benefits package. A candidate’s salary is determined by various factors, including but not limited to education, relevant work experience, skills, and certifications. Salary ranges may vary based on geographic location and market conditions.
\#LI\-TF1
Benefits: Live an Extraordinary Life
We care about your well\-being, not just on the job. Battelle offers comprehensive and competitive benefits to help you live your best life.
- Balance life through a compressed work schedule: Most of our team follows a flexible, compressed work schedule that allows for every other Friday off—giving you a dedicated day to accomplish things in your personal life without using vacation time.
- Enjoy enhanced work flexibility, including a hybrid arrangement: You have options for where and when you work. Our Together with Flexibility model allows you to work 60% in\-office and 40% remote, with Monday and Tuesday as common in\-office days, dependent on team and position needs.
- Take time to recharge: You get paid time off to support work\-life balance and keep motivated.
- Prioritize wellness: Stay healthy with medical, dental, and vision coverage with wellness incentives and benefits plus a variety of optional supplemental benefits.
- Better together: Coverage for partners, gender\-affirming care and health support, and family formation support.
- Build your financial future: Build financial stability with an industry\-leading 401(k) retirement savings plan. For most employees, we put in 5 percent whether you contribute or not, and match your contributions on top of that.
- Advance your education: Tuition assistance is available to pursue higher education.
A Work Environment Where You Succeed
For brilliant minds in science, technology, engineering and business operations, Battelle is the place to do the greatest good by solving humanity’s most pressing challenges and creating a safer, healthier and more secure world.
You will have the opportunity to thrive in a culture that inspires you to:
- Apply your talent to challenging and meaningful projects
- Receive select funding to pursue ideas in scientific and technological discovery
- Partner with world\-class experts in a collaborative environment
- Nurture and develop the next generation of scientific leaders
- Give back to and improve our communities
Vaccinations \& Safety Protocols
*Battelle may require employees, based on job duties, work location, and/or its clients’ requirements to follow certain safety protocols and to be vaccinated against a variety of viruses, bacteria, and diseases as a condition of employment and continued employment and to provide documentation that they are fully vaccinated. If applicable, Battelle will provide reasonable accommodations based on a qualified disability or medical condition through the Americans with Disabilities Act or the Rehabilitation Act or for a sincerely held religious belief under Title VII of the Civil Rights Act of 1964 (and related state laws).*
*Battelle is an equal opportunity employer. We provide employment and opportunities for advancement, compensation, training, and growth according to individual merit, without regard to race, color, religion, sex (including pregnancy), national origin, sexual orientation, gender identity or expression, marital status, age, genetic information, disability, veteran\-status veteran or military status, or any other characteristic protected under applicable Federal, state, or local law. Our goal is for each staff member to have the opportunity to grow to the limits of their abilities and to achieve personal and organizational objectives. We will support positive programs for equal treatment of all staff and full utilization of all qualified employees at all levels within Battelle.*
The above statements are intended to describe the nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, activities and skills required of staff members. No statement herein is intended to imply any authorities to commit Battelle unless special written permission is granted by Battelle's Legal Department.
For more information about our other openings, please visit www.battelle.org/careers
Salary Context
This $72K-$100K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $184K across 1486 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 2,799 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Battelle, 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 $175,000 based on 11,128 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $97,760. This role's midpoint ($86K) sits 51% below the category median. Disclosed range: $72K to $100K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,760; Mid: $159,385; Senior: $227,500; Director: $242,000; VP: $250,000.
Battelle AI Hiring
Battelle has 2 open AI roles right now. They're hiring across Data Scientist, AI/ML Engineer. Positions span Crystal City, VA, US, Columbus, OH, US. Compensation range: $100K - $100K.
Location Context
Across all AI roles, 16% (460 positions) offer remote work, while 2,318 require on-site attendance. Top AI hiring metros: New York (2,241 roles, $208,300 median); San Francisco (1,822 roles, $252,000 median); Los Angeles (1,611 roles, $188,900 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 2,799 open positions tracked in our dataset. By seniority: 98 entry-level, 1,283 mid-level, 1,092 senior, and 326 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (460 positions). The remaining 2,318 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $252,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 30 roles); AI Safety ($274,200 median, 43 roles); Research Engineer ($260,000 median, 387 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 2,799 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (1,978), AI Software Engineer (197), Data Scientist (195). 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 (98) are outnumbered by mid-level (1,283) and senior (1,092) 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 326 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (460 positions), with 2,318 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 $200,000. Top-quartile roles start at $252,000, and the 90th percentile reaches $307,500. 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 $142,800. 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 (1,433 postings), Aws (840 postings), Rag (663 postings), Azure (639 postings), Gcp (537 postings), Pytorch (445 postings), Prompt Engineering (418 postings), Claude (396 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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