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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
We are currently seeking an AI/ML Engineer – Entry Level. This position is a full-time opportunity located in Columbus, Ohio.
Battelle is seeking an AI/ML Engineer – Entry Level to help improve laboratory efficiency through practical AI, automation, and data solutions. Working alongside scientists, technicians, quality staff, and technology teams, this role will identify repetitive or time-consuming work and develop tools that simplify laboratory workflows, reduce manual and redundant efforts, improve data quality, and support faster, more consistent operations — while capturing data for use in larger AI and machine learning initiatives.
This is a hands-on learning role. Initial projects may include AI-assisted data review, sample and inventory tracking, workflow automation, dashboards, laboratory scheduling, document search, and tools that help staff access and use laboratory information more effectively.
Responsibilities
As an AI/ML Engineer – Entry Level, the selected individual will develop and deploy practical AI and automation solutions that enhance laboratory operations and data quality. Responsibilities may include:
- Assist with building practical AI tools, low-code applications, dashboards, forms, and automated workflows using approved platforms
- Help organize and analyze laboratory data to improve sample tracking, inventory, scheduling, instrument utilization, reporting, and turnaround time
- Learn and document laboratory workflows to identify bottlenecks, manual steps, and opportunities for AI or automation
- Use approved tools such as Microsoft Copilot, Copilot Studio, Visual Studio, Power Automate, Power Apps, Power BI, SharePoint, Python, and SQL
- Support integration among laboratory systems, instrument data, spreadsheets, databases, and business applications
- Help develop and maintain internal data management systems and electronic notebooks across multiple laboratory environments
- Participate in requirements gathering, testing, validation, documentation, training, and end-user support
- Capture and report metrics such as time saved, reduced manual entries, fewer errors, improved data access, and increased user adoption
- Follow requirements for cybersecurity, data protection, responsible AI, quality, safety, and change control within both internal and client frameworks
Key Qualifications
- Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Chemistry, Biology, Laboratory Science, or a related field; or an equivalent combination of education and experience
- Zero to two years of relevant experience, including internships, co-ops, research, coursework, or significant projects
- Interest in applying AI, data, software, or automation to improve laboratory operations
- Foundational experience with one or more of the following: Microsoft Power Platform, generative AI tool use and development, Python, SQL, data visualization, workflow automation, or application development
- Ability to learn laboratory processes, collaborate with end users, solve practical problems, and communicate clearly
- Basic understanding of data quality, testing, documentation, and the responsible use of technology
- [INSERT TRAVEL REQUIREMENTS]
- Applicants must have authorization to work in the United States. We are unable to sponsor or take over sponsorship of any employment Visa at this time.
Preferred Qualifications
- Laboratory, research, manufacturing, environmental, healthcare, or other technical operating experience
- Exposure to LIMS, electronic laboratory notebooks, scientific instruments, sample tracking, inventory, or quality systems
- Experience developing AI-assisted tools, prompts, workflows, dashboards, or applications through coursework or projects
- Familiarity with Lean, Six Sigma, process mapping, root-cause analysis, Git, APIs, or cloud services
Compensation Data
Battelle is committed to fair and equitable compensation practices. The salary range for this role is $71,200 – $101,400 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.
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 $71K-$101K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% 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 $211,950 based on 13,048 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $111,000. This role's midpoint ($86K) sits 59% below the category median. Disclosed range: $71K to $101K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Battelle AI Hiring
Battelle has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Columbus, OH, US. Compensation range: $101K - $101K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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