Machine Learning Engineer Visa Sponsorship Jobs in Ohio
Ohio's machine learning engineer job market is anchored by employers in Columbus, Cleveland, and Cincinnati, with major tech, healthcare, and financial services companies actively hiring. JPMorgan Chase, Nationwide, and major healthcare systems like Cleveland Clinic have sponsored ML engineering roles. Ohio's research universities also feed a steady pipeline of ML talent into the state's growing tech sector.
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INTRODUCTION
At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use. Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together. We're seeking passionate ML Engineers to join our team at the intersection of welding science and artificial intelligence. We currently have experienced (L3/L4), senior (L5) and staff (L6) level openings within and you'll be instrumental in developing robotic welding solutions. You'll use your skills in computer vision, deep learning, and Python programming to tackle challenges in our field alongside our talented teams.
ROLE AND RESPONSIBILITIES
Experienced:
- Implement, validate, and iterate on machine learning algorithms for weld perception tasks, including point cloud registration, seam detection, and joint geometry estimation, progressively expanding coverage across joint types and part geometries.
- Build and maintain data pipelines for training and evaluating perception models, spanning annotated 3D scan data ingestion, synthetic data generation, and structured dataset management for iterative model improvement.
- Run rigorous model evaluation experiments, including failure mode analysis, FP/FN rate characterization, and benchmarking against quantitative registration accuracy thresholds, and communicate findings clearly to guide next steps.
- Integrate trained models into production ROS-based robotics services, ensuring low-latency inference and compatibility with deployed cell configurations.
- Write clean, well-tested Python code; participate actively in code and experiment reviews; and maintain clear documentation of methods, parameters, and results.
Senior/Staff:
- Lead research, development, and production deployment of advanced perception algorithms spanning point cloud registration, seam detection, and real-time in-process tracking across structured light, RGB, and stereo sensors.
- Design and lead experiments evaluating state-of-the-art deep learning models, including transformer-based and geometric feature learning architectures.
- Design and lead real-time perception systems such as during-weld seam tracking, applying sensor fusion with probabilistic state estimation (e.g., Kalman filtering) to achieve robust weld performance.
- Define and own the end-to-end ML lifecycle, from dataset design and annotation strategy through training, benchmarking, and fleet deployment, with clear go/no-go evaluation frameworks.
- Architect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic vs. real scan data usage.
- Mentor engineers across levels, providing technical leadership on perception systems and ML methodology.
BASIC QUALIFICATIONS
- Master's or Ph.D. in CS, Robotics, or related field (Computer Vision, ML, or Perception); Bachelor's with strong production ML experience also considered.
- 3+ years (Experienced) / 7+ years (Senior/Staff) in real-world robotics or industrial ML.
- Strong Python fluency and hands-on PyTorch experience, including training, evaluating, and deploying deep learning models in production.
- Experience with 3D point cloud data and libraries such as Open3D, including geometric concepts like surface segmentation, spatial queries, and point-wise labeling.
- Familiarity with 3D deep learning architectures such as PointNet++, GeoTransformer, or similar transformer-based or graph-based approaches on geometric data.
- Comfortable integrating ML models into production robotics services within ROS-based architectures and containerized deployment environments.
- Senior/Staff: Demonstrated track record leading end-to-end ML projects from dataset design through fleet deployment with rigorous go/no-go frameworks; experience architecting distributed training and hyperparameter optimization workflows.
WHY YOU’LL LOVE WORKING HERE
- Daily free lunch to keep you fueled and connected with the team
- Flexible PTO so you can take the time you need, when you need it
- Comprehensive medical, dental, and vision coverage
- 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
- 401(k) retirement plan through Empower
- Generous employee referral bonuses—help us grow our team!
WHO WE ARE
At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

INTRODUCTION
At Path Robotics, we’re building the future of embodied intelligence. Our AI-driven systems enable robots to adapt, learn, and perform in the real world closing the skilled labor gap and transforming industries. We go beyond traditional methods, combining perception, reasoning, and control to deliver field-ready AI that is risk-aware, reliable, and continuously improving through real-world use. Big, hard problems are our everyday work, and our team of intelligent, humble, and driven people make the impossible possible together. We're seeking passionate ML Engineers to join our team at the intersection of welding science and artificial intelligence. We currently have experienced (L3/L4), senior (L5) and staff (L6) level openings within and you'll be instrumental in developing robotic welding solutions. You'll use your skills in computer vision, deep learning, and Python programming to tackle challenges in our field alongside our talented teams.
ROLE AND RESPONSIBILITIES
Experienced:
- Implement, validate, and iterate on machine learning algorithms for weld perception tasks, including point cloud registration, seam detection, and joint geometry estimation, progressively expanding coverage across joint types and part geometries.
- Build and maintain data pipelines for training and evaluating perception models, spanning annotated 3D scan data ingestion, synthetic data generation, and structured dataset management for iterative model improvement.
- Run rigorous model evaluation experiments, including failure mode analysis, FP/FN rate characterization, and benchmarking against quantitative registration accuracy thresholds, and communicate findings clearly to guide next steps.
- Integrate trained models into production ROS-based robotics services, ensuring low-latency inference and compatibility with deployed cell configurations.
- Write clean, well-tested Python code; participate actively in code and experiment reviews; and maintain clear documentation of methods, parameters, and results.
Senior/Staff:
- Lead research, development, and production deployment of advanced perception algorithms spanning point cloud registration, seam detection, and real-time in-process tracking across structured light, RGB, and stereo sensors.
- Design and lead experiments evaluating state-of-the-art deep learning models, including transformer-based and geometric feature learning architectures.
- Design and lead real-time perception systems such as during-weld seam tracking, applying sensor fusion with probabilistic state estimation (e.g., Kalman filtering) to achieve robust weld performance.
- Define and own the end-to-end ML lifecycle, from dataset design and annotation strategy through training, benchmarking, and fleet deployment, with clear go/no-go evaluation frameworks.
- Architect distributed training and hyperparameter optimization workflows; drive strategy for data acquisition, annotation tooling, and synthetic vs. real scan data usage.
- Mentor engineers across levels, providing technical leadership on perception systems and ML methodology.
BASIC QUALIFICATIONS
- Master's or Ph.D. in CS, Robotics, or related field (Computer Vision, ML, or Perception); Bachelor's with strong production ML experience also considered.
- 3+ years (Experienced) / 7+ years (Senior/Staff) in real-world robotics or industrial ML.
- Strong Python fluency and hands-on PyTorch experience, including training, evaluating, and deploying deep learning models in production.
- Experience with 3D point cloud data and libraries such as Open3D, including geometric concepts like surface segmentation, spatial queries, and point-wise labeling.
- Familiarity with 3D deep learning architectures such as PointNet++, GeoTransformer, or similar transformer-based or graph-based approaches on geometric data.
- Comfortable integrating ML models into production robotics services within ROS-based architectures and containerized deployment environments.
- Senior/Staff: Demonstrated track record leading end-to-end ML projects from dataset design through fleet deployment with rigorous go/no-go frameworks; experience architecting distributed training and hyperparameter optimization workflows.
WHY YOU’LL LOVE WORKING HERE
- Daily free lunch to keep you fueled and connected with the team
- Flexible PTO so you can take the time you need, when you need it
- Comprehensive medical, dental, and vision coverage
- 6 weeks fully paid parental leave, plus an additional 6–8 weeks for birthing parents (12–14 weeks total)
- 401(k) retirement plan through Empower
- Generous employee referral bonuses—help us grow our team!
WHO WE ARE
At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Machine Learning Engineer Job Roles in Ohio
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Search Machine Learning Engineer Jobs in OhioMachine Learning Engineer Jobs in Ohio: Frequently Asked Questions
Which companies sponsor visas for machine learning engineers in Ohio?
Several large Ohio-based employers have a documented history of sponsoring work visas for machine learning engineers. JPMorgan Chase and Discover Financial in Columbus, Progressive Insurance in Mayfield Village, and Cleveland Clinic in the healthcare sector have all filed Labor Condition Applications for ML and data science roles. Large tech divisions of retailers like Big Lots and consulting firms with Ohio offices also appear in federal sponsorship disclosure data.
Which visa types are most common for machine learning engineer roles in Ohio?
The H-1B visa is the most common sponsorship pathway for machine learning engineers in Ohio, as ML roles consistently qualify as specialty occupations requiring at least a bachelor's degree in computer science, statistics, or a related technical field. Candidates with an Australian passport may qualify for the E-3 visa. Those with extraordinary ability or a national interest waiver petition may pursue O-1 or EB-2 NIW pathways without requiring employer-sponsored PERM.
Which cities in Ohio have the most machine learning engineer sponsorship jobs?
Columbus is Ohio's primary hub for ML engineering sponsorship, driven by its concentration of financial services firms, insurance companies, and a growing tech sector anchored by companies like Nationwide and JPMorgan Chase. Cleveland follows, with healthcare and manufacturing technology employers sponsoring ML roles. Cincinnati has a smaller but active market through consumer goods companies and regional financial institutions. All three cities have universities that create local hiring pipelines.
How to find machine learning engineer visa sponsorship jobs in Ohio?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search machine learning engineer roles in Ohio without sifting through postings from employers who don't sponsor. The platform surfaces roles from companies with verified sponsorship histories in the state. This is especially useful for H-1B and E-3 candidates who need to identify employers willing to file petitions before investing time in the application process.
Are there any Ohio-specific factors that affect visa sponsorship for machine learning engineers?
Ohio's lower cost of living compared to coastal tech hubs means prevailing wage benchmarks set by the Department of Labor are generally lower than in San Francisco or New York, which can make sponsorship more financially accessible for Ohio employers. The state's strong university system, including Ohio State University and Case Western Reserve, produces ML graduates who sometimes transition from OPT into sponsored roles with local employers, making campus recruiting a notable pipeline for sponsored positions.
What is the prevailing wage for sponsored machine learning engineer jobs in Ohio?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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