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Remote No Experience Machine Learning Jobs in Ohio

micro1 AI

AI Trainer - Microbiology Expert

Akron, OH · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

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Remote No Experience Machine Learning information

What are some typical entry-level tasks for remote machine learning roles that require no prior experience?

In remote entry-level machine learning positions that don't require experience, you'll often start with foundational tasks such as data cleaning, labeling datasets, basic exploratory data analysis, or assisting with the implementation of machine learning algorithms under supervision. You may also be responsible for maintaining project documentation and supporting more experienced team members with research or testing. Collaboration usually takes place via online platforms, so strong communication and the ability to learn new tools quickly are important. These tasks are designed to help you build foundational skills and gradually take on more complex responsibilities as you grow in the role.

What are the key skills and qualifications needed to thrive in a remote, entry-level machine learning role?

To thrive in a remote, entry-level machine learning role, you need a solid understanding of mathematics, programming (especially Python), and basic machine learning concepts, often gained through online courses or a relevant degree. Familiarity with technical tools such as Jupyter Notebooks, TensorFlow, or scikit-learn, and experience using version control systems like Git are commonly expected. Strong self-motivation, effective communication, and the ability to collaborate virtually make candidates stand out in remote environments. These skills and qualities are crucial for successfully contributing to projects, adapting to new technologies, and working efficiently with distributed teams.

What is the difference between Remote No Experience Machine Learning vs Remote No Experience Data Analysis?

AspectRemote No Experience Machine LearningRemote No Experience Data Analysis
Required CredentialsBasic understanding of programming, statistics, and data concepts; no formal certification neededBasic knowledge of data handling, Excel, and analytical tools; no formal certification needed
Work EnvironmentRemote, often collaborative with data science teamsRemote, often independent or team-based data review tasks
Industry UsageUsed in tech, finance, healthcare for predictive modelingUsed across industries for reporting, insights, and decision-making

While both roles are entry-level and remote, Machine Learning focuses on understanding algorithms and predictive models, whereas Data Analysis emphasizes interpreting data and generating reports. Your choice depends on whether you prefer working with algorithms and coding or analyzing data for insights.

What are popular job titles related to Remote No Experience Machine Learning jobs in Ohio?

For Remote No Experience Machine Learning jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Remote No Experience Machine Learning jobs in Ohio look for?

The top searched job categories for Remote No Experience Machine Learning jobs in Ohio are:

What cities in Ohio are hiring for Remote No Experience Machine Learning jobs?

Cities in Ohio with the most Remote No Experience Machine Learning job openings:

Remote No Experience Machine Learning jobs near you

Senior Machine Learning Engineer (Reinforcement Learning/World Model)

Columbus, OH • On-site, Remote

Path Robotics
Industrial Automation Equipment Manufacturing • 201 - 500 employees
Learn more about Path Roboticsexternal

$100K - $138K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 27 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.
Manufacturing demands exceptionally high performance, reliability, and adaptability. Processes like welding involve fast, complex, and poorly modeled physics that traditional simulators struggle to capture - especially in the long tail of real-world conditions.
We are building intelligent robotic systems that learn directly from data by combining neural world models with reinforcement learning. Our goal is to give robots the ability to learn, predict, and plan in complex manufacturing environments by replacing or augmenting classical physics simulators with fast, high-fidelity learned ones.
We are seeking a Senior Machine Learning Engineer to lead the development of a neural welding simulator - a learned world model that captures the visual and physical dynamics of welding and enables large-scale RL training. This role sits at the intersection of generative modeling, robotics, and applied physics. It is research-heavy by design, while still grounded in production reality.
We are hiring two Senior Machine Learning Engineers with complementary specializations:
  • Senior Machine Learning Engineer, World Models
  • Senior Machine Learning Engineer, Reinforcement Learning
Senior ML Engineer, World Models
What You'll Do
  • Build action-conditioned world models that predict how the welding process evolves under changes to robot motion and process parameters.
  • Model relationships among inputs, system state, physical dynamics, and resulting weld quality.
  • Develop multimodal models using data such as video, 3D scans, thermal measurements, electrical signals, robot state, and process parameters.
  • Explore latent dynamics, video prediction, generative modeling, and spatiotemporal representations.
  • Improve long-horizon rollout accuracy, physical plausibility, temporal consistency, and computational efficiency.
  • Quantify model uncertainty and identify conditions under which predictions are unreliable.
  • Validate learned predictions against real-world welding data.
  • Integrate the model into RL, planning, process-optimization, evaluation, and synthetic-data workflows.
  • Prevent downstream optimization systems from exploiting inaccuracies in the learned model.
  • Translate promising research into scalable training and inference systems.
Senior ML Engineer, Reinforcement Learning
What You'll Do
  • Develop reinforcement learning approaches for optimizing welding decisions and process outcomes.
  • Define state, observation, action, and reward representations based on measurable manufacturing objectives.
  • Train and evaluate policies using learned world models, traditional simulation, offline datasets, and controlled real-world experiments.
  • Develop offline, model-based, or constrained RL methods suitable for limited and expensive physical interaction.
  • Optimize across competing objectives such as weld quality, cycle time, reliability, energy use, and equipment constraints.
  • Design methods that account for uncertainty, distribution shift, delayed outcomes, and sparse or imperfect reward signals.
  • Diagnose reward exploitation, unsafe behavior, policy instability, and model exploitation.
  • Establish reliable offline and real-world policy evaluation methods.
  • Partner with controls, welding, robotics, world-model, data, and ML infrastructure engineers.
  • Translate research prototypes into dependable training, evaluation, and deployment systems.
Who You Are
  • Master's or PhD in Computer Science, Robotics, Machine Learning, or related field, or equivalent practical experience.
  • Experience developing and deploying reinforcement learning algorithms on real-world systems.
  • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with simulation environments (e.g., MuJoCo, Isaac Gym).
  • Solid understanding of probability, statistics, and optimization.
  • Experience with training and deploying ML models in production systems.
Why You'll Love It 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 HR@path-robotics.com. 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.

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