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Entry Level Machine Learning Engineer Jobs in Ohio

2nd shift Machine Operator

Avon, OH · On-site

$17.07 - $21.66/hr

Kickstart Your Manufacturing Career! Entry-Level Machine Operator Looking to get your foot in the ... Enjoys learning new equipment * Takes pride in quality work Apply today and start building a career ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Akron, OH · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

$120 - $180/hr

Strong software engineering fundamentals and experience building production systems * Experience building ML infrastructure, platforms, or production machine learning systems * Experience with model ...

As an AI Engineer, you will be responsible for designing, implementing, testing and maintaining ... The ideal candidate will have a strong background in AI, machine learning and data science, with ...

Showing results 41-60

Entry Level Machine Learning Engineer information

See Ohio salary details

$28.5K

$65.9K

$112.2K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for entry level machine learning engineer in Ohio is $65,942.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $74,600.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are the most commonly searched types of Machine Learning Engineer jobs in Ohio?

The most popular types of Machine Learning Engineer jobs in Ohio are:

What cities in Ohio are hiring for Entry Level Machine Learning Engineer jobs?

Cities in Ohio with the most Entry Level Machine Learning Engineer job openings:

Infographic showing various Entry Level Machine Learning Engineer job openings in Ohio as of August 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $65,942 per year, or $31.7 per hour.

Machine Learning Engineer, Robot Learning, Loco-Manipulation

Path Robotics

Columbus, OH • On-site

Other

Medical, Dental, Vision, Retirement, PTO

Re-posted 21 days ago


Job description

Build the Path Forward
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 are standing up a new Robot Learning team focused on whole-body loco-manipulation for precision tasks in heavy manufacturing.
We are seeking a Machine Learning Engineer to join us as a founding member. You will be among the first ML engineers on a research stack that does not exist anywhere else in the field built around visual reasoning, learned action policies, and reinforcement-learning fine-tuning from real customer data.
What You'll Do
  • Build the team's robot-learning stack from the ground up. This is a founding role; you are designing the training infrastructure, data pipelines, simulation environments, model architectures, and deployment workflows - not inheriting them. Multi-modal perception, scene understanding, and learned action generation work in tight coordination on the stack you help create.
  • Stand up ML infrastructure - training pipelines, experiment tracking, data versioning, reproducible sim-to-real workflows.
  • Train policies across manipulation, locomotion, and the whole-body control coupling between them. On legged platforms performing precision tasks, manipulation and locomotion are not separable - every arm motion shifts the centre of mass; the whole-body controller compensates in real time to maintain accuracy at the tool. Behavioural cloning, diffusion- and flow-matching action generation, reinforcement-learning fine-tuning. Cobots, industrial arms, and mobile platforms.
  • Deploy in stages - through a phased rollout strategy that builds production trust over time. Every real-world execution accumulates training data for continuous improvement.
  • Collaborate daily with mechanical engineers, perception engineers, robotics engineers, and manufacturing domain experts. Within-department rotation across home teams is expected.

Who You Are
  • Ph.D. or Master's degree in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field - or equivalent experience.
  • 2+ years of hands-on robot learning experience. You have trained policies and deployed them on real robot hardware - not just in simulation.
  • Sim-to-real transfer experience - built simulation environments, implemented domain randomisation, transferred policies to physical robots, debugged where it broke.
  • Implementation experience with diffusion-based or flow-matching action policies for robots, and with action chunking.
  • Reinforcement learning for robotics applied on real hardware - sample-efficient on-robot methods, residual RL on top of pretrained policies, on-policy fine-tuning of foundation policies.
  • Strong programming skills in Python; PyTorch and ML training infrastructure at production level.
  • Practical experience with NVIDIA Isaac Sim / Isaac Lab, MuJoCo, or equivalent.
  • Comfort with physical robots - debugging, iterating, deploying.
  • Strong communication skills, able to convey complex technical concepts to a diverse audience.

Strongly Preferred:
  • Edge inference on edge-class hardware (TensorRT, ONNX, FP16 / INT8 quantisation). Real-time on-robot deployment is a core requirement.
  • Visual self-supervised representation learning experience on robot or 3D-vision tasks.
  • Legged-robot or whole-body control experience - locomotion, manipulation on a floating base, or the integration between them on quadrupeds or humanoids.
  • Physics-informed ML - hybrid models where learned components are constrained by known physics.
  • Experience building ML pipelines or infrastructure in a team setting.

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.
If you require a reasonable accommodation to participate in the application process or any part of the hiring process, please contact We are committed to providing equal access and will work with qualified individuals to ensure a fair and accessible hiring experience. We will respond to your request within 48 hours.