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About This Role
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.
At Battelle, interns and co\-ops make an impact through hands\-on learning and exciting and challenging projects. Our interns are an integral part of the teams they support and will feel like they are a true, valued team member. 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.
A brighter future is possible with *you*.
Job Summary
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Battelle is seeking a Data Science Co\-Op for Spring and/or Summer Semester 2026. This position is 100% onsite, full\-time, located in Columbus, OH, and supports Battelle’s Cyber Trust \& Assurance division, in our National Security Global Business.
Do you like developing and applying analytics tools to unconventional problems, working on research projects you are passionate about, and competitive mini basketball, and bumper pool? Battelle may be the company for you.
Battelle cyber analytics experts solve the toughest data science problems in the world. We work in small agile teams to push the bounds of computing technology. Our high\-powered computer labs include specialized software and hardware, so our engineers have everything they need to invent new Cyber solutions.
Our team is casual. We usually wear t\-shirts and jeans. We are a close\-knit group and enjoy participating in social activities outside of work. Whether it is visiting local restaurants, bowling, Korean BBQ, or paintball we always have a good time.
Battelle is committed to its employee’s professional growth. We encourage new ideas with our large Internal Research and Development (IRAD) program where engineers work on projects they are passionate about.
Responsibilities
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- Aid in the design and implementation of machine learning, data mining, data fusion, and data engineering techniques applied to cyber microelectronics security problems
- Assess the security, reliability, and trustworthiness of electronic devices, integrated circuits, and embedded systems
- Support the latest Cyber Trust and Analytics team’s research and development programs
- Learn and improve your engineering skills through project and team building activities
- Conduct and / or participate in assigned technical tasks and activities with minimum supervision and within time and budget constraints.
- Work independently and effectively in a multi\-disciplinary team environment
- Effectively communicate ideas with other engineers
Key Qualifications
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- Currently enrolled in a bachelor’s, Master’s or Doctorate degree program in Data Science, Physics, Computer Engineering, Materials Science, Statistics, Mathematics, Systems Engineering or related field of study
- At least 1\-year of college\-level coursework completed
- Experience with high\-level software languages such as Python, R, or MATLAB
- Basic machine/statistical learning approaches and validation techniques
- Ability to demonstrate organization, communication, problem\-solving, and teamwork skills
- Interest in one or more of the following areas:
+ - Digital design and microcontrollers
- VLSI Integrated circuit design
- Semiconductor device fabrication / physics
- Integrated circuit failure analysis
- Deep neural network approaches
- Signal Processing
- Machine learning on graphs
- Cryptography
- Data integration (e.g., Hierarchical Bayes)
- Must be a U.S. Citizen with the ability to obtain and maintain a US government security clearance
Preferred Qualifications
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- Ability to apply learned skills to real\-life scenarios (e.g., research, publication, blogs, GitHub, Arxiv, Kaggle competitions, internships, hack\-a\-thons, cybersecurity clubs, CTFs, etc.)
- Reverse engineering embedded hardware and software
- Programming and using data acquisition tools
- Experience with one or more of the following areas:
+ - Big data methods
- Databases (SQL, NOSQL, graph DB)
- Writing or debugging software code in C or C\+\+ or C\#
- Reverse engineering hardware or software
- CAD or layout experience
- VLSI design coursework
- FPGA design workflows
- Microcontroller design and assembly languages
- Semiconductor fabrication and analysis processes
Compensation Data
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Battelle is committed to fair and equitable compensation practices. The hourly range for this role is $20 \- $40\. 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.
Preparing You for Career Success
The Battelle intern and co\-op program is a great way to increase experience both on a team and as an independent contributor. Ninety\-eight percent of internship survey respondents said they felt better prepared to enter the workforce after their Battelle internship and 100% said they were treated with respect by their colleagues.
You will have the opportunity to thrive in a culture that inspires you to:
- Apply your talent to challenging and meaningful projects
- Pursue ideas in scientific and technological discovery
- Partner with world\-class experts in a collaborative environment
- Become the next generation of scientific leaders and business professionals
Are you ready to help solve the most important challenges of today and tomorrow?
If so, we are ready to support you with:
- Flexible work schedules: Most teams follow a flexible, compressed work schedule that allows for every other Friday off
- 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.
- Employee Resource Groups that help cultivate an inclusive and welcoming community
- Social and professional networking events with Battelle Senior Leadership and your colleagues
- Opportunities for philanthropic involvement to give back and make an impact in the community
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 $41K-$83K range is in the lower quartile 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 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($62K) sits 71% below the category median. Disclosed range: $41K to $83K.
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.
Battelle AI Hiring
Battelle has 2 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer. Based in Columbus, OH, US. Compensation range: $83K - $105K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 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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