1

Machine Learning Developer Intern Jobs in Ohio (NOW HIRING)

$140 - $190/hr

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights. This role sits at the ...

New

Machine Learning Engineer II

Columbus, OH

$94K - $128K/yr

Machine Learning II Engineer - Incydr Product Development Mimecast is at the forefront of the cybersecurity industry, delivering innovative solutions to protect businesses and individuals from ...

Machine Learning Engineer II

Columbus, OH · On-site

$94K - $128K/yr

Machine Learning II Engineer - Incydr Product Development Mimecast is at the forefront of the cybersecurity industry, delivering innovative solutions to protect businesses and individuals from ...

They will gain an understanding of the retail business by learning and completing skill level ... Gain experience and exposure to hand sewing and machine sewing projects. * Experience the art of ...

They will gain an understanding of the retail business by learning and completing skill level ... Gain experience and exposure to hand sewing and machine sewing projects. * Experience the art of ...

$18.50 - $24.25/hr

As a Gen Ai developer Intern you will be trained to deliver a POC/POT/MVP by designing, developing ... However, the learning does not stop there! TCS is committed to the continuous growth of its ...

Gen AI Developer Intern

Dublin, OH · On-site

$18.50 - $24.50/hr

As a Gen Ai developer Intern you will be trained to deliver a POC/POT/MVP by designing, developing ... However, the learning does not stop there! TCS is committed to the continuous growth of its ...

$18.50 - $24.50/hr

As a Gen Ai developer Intern you will be trained to deliver a POC/POT/MVP by designing, developing ... However, the learning does not stop there! TCS is committed to the continuous growth of its ...

Machine Learning Engineer

Beavercreek, OH · On-site

$51.75 - $68.50/hr

Etegent is seeking Machine Learning Engineers (MLEs) to work with our Intelligence, Surveillance, and Reconnaissance (ISR) group based in the Beavercreek office. MLEs will work in a team environment ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Showing results 21-40

Machine Learning Developer Intern information

What does a machine learning developer intern do?

A Machine Learning Developer Intern assists with developing, testing, and implementing machine learning models and algorithms under the guidance of experienced engineers or data scientists. Their tasks may include data preprocessing, model training, evaluating model performance, and helping deploy models into production environments. Interns often collaborate with team members to solve real-world problems using machine learning techniques and may also assist in researching new methodologies or optimizing existing solutions. This role provides hands-on experience in coding, data analysis, and applying theoretical concepts to practical scenarios.

What are the key skills and qualifications needed to thrive as a machine learning developer intern?

To thrive as a Machine Learning Developer Intern, you need a solid understanding of programming (especially Python), statistics, and machine learning concepts, often supported by coursework or relevant project experience. Familiarity with ML frameworks like TensorFlow or PyTorch, and tools such as Jupyter Notebooks and version control systems like Git, is typically expected. Strong analytical thinking, eagerness to learn, and effective communication help interns contribute to team projects and adapt quickly. These skills are essential for solving real-world problems, collaborating with teams, and building a foundation for a successful career in machine learning.

How do machine learning developer interns typically collaborate with data scientists and engineers during their internship?

Machine Learning Developer Interns often work closely with data scientists to understand the problem domain, gather relevant datasets, and select appropriate models. They also collaborate with software engineers to integrate machine learning solutions into existing systems, ensuring scalability and performance. Regular communication through stand-up meetings, code reviews, and collaborative platforms is common, allowing interns to learn best practices and receive feedback on their work. This teamwork not only enhances technical skills but also provides valuable exposure to real-world deployment and project lifecycle management.

What is the difference between Machine Learning Developer Intern vs Data Scientist Intern?

AspectMachine Learning Developer InternData Scientist Intern
Required CredentialsTypically pursuing or recently completed a degree in Computer Science, Data Science, or related fields; knowledge of programming languages like Python or JavaSimilar educational background; strong skills in statistics, programming, and data analysis
Work EnvironmentHands-on experience with ML models, algorithms, and software development in tech or research settingsData analysis, visualization, and interpretation in business or research contexts
Employer & Industry UsageTech companies, startups, research labs focusing on AI/ML projectsBusiness, finance, healthcare, and research organizations analyzing large datasets

Both roles involve working with data and programming, but Machine Learning Developer Interns focus more on building and deploying ML models, while Data Scientist Interns emphasize data analysis and insights. The roles often overlap, especially in tech environments, but their core tasks differ slightly.

What cities in Ohio are hiring for Machine Learning Developer Intern jobs?

Cities in Ohio with the most Machine Learning Developer Intern job openings:

Senior Geospatial Machine Learning Engineer

Jobgether

On-site

$140 - $190/hr

Other

Posted yesterday

New


Job description

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights.
This role sits at the intersection of machine learning, geospatial technology, and climate innovation, helping solve complex challenges impacting critical infrastructure.
You will work on building and improving algorithms that analyze vegetation, assess risks, and support smarter decision-making for energy systems.
The position offers the opportunity to own impactful projects from experimentation through production while collaborating with multidisciplinary engineering and scientific teams.
You will contribute to the evolution of data-driven products using cutting-edge ML techniques, remote sensing data, and geospatial technologies.
This is an ideal opportunity for an experienced engineer passionate about applying AI to create meaningful environmental impact.

Accountabilities:

The Senior Geospatial Machine Learning Engineer will design, develop, and improve machine learning solutions that leverage geospatial data to deliver innovative environmental intelligence products. This role requires strong technical ownership, collaboration, and the ability to translate complex data challenges into practical solutions.

  • Develop new geospatial intelligence products using Python-based geospatial libraries, machine learning, and deep learning techniques.
  • Improve existing solutions through data exploration, model optimization, debugging, and performance enhancements.
  • Work with satellite and aerial imagery, raster and vector datasets, and geospatial workflows to solve real-world challenges.
  • Lead technical projects from planning and experimentation through implementation, delivery, and stakeholder communication.
  • Build tools and processes to evaluate model performance, product impact, and data-driven prioritization.
  • Collaborate with data engineering, product, platform, and delivery teams throughout the full machine learning product lifecycle.
  • Contribute to technical direction, engineering practices, and team culture within a fast-growing environment.
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Requirements:

The ideal candidate is an experienced machine learning or geospatial engineer with strong expertise in Python, scientific computing, and applied AI. They should be comfortable working independently, leading projects, and applying advanced technology to environmental and infrastructure challenges.

  • 8–10+ years of experience in machine learning engineering, geospatial engineering, remote sensing, or a closely related technical field.
  • Strong Python programming skills with hands-on experience using geospatial libraries such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas.
  • Experience with scientific Python tools including NumPy, SciPy, scikit-learn, and Pandas.
  • Practical experience developing deep learning solutions using frameworks such as PyTorch and/or TensorFlow.
  • Strong understanding of satellite imagery, aerial imagery, and geospatial raster/vector data processing.
  • Experience with workflow orchestration tools such as Dagster or similar platforms.
  • Ability to independently lead initiatives, manage technical projects, and communicate results effectively.
  • Passion for climate technology and using machine learning to address complex environmental problems.

Nice-to-have qualifications:

  • Experience with vegetation science, forestry, energy infrastructure, or utility-related technologies.
  • Familiarity with observability tools such as Sentry and Grafana.
  • Previous experience in climate tech, geospatial AI, remote sensing, or environmental data companies.
Benefits:
  • Fully remote work environment with flexibility across eligible locations.
  • Opportunity to work on impactful climate technology projects using AI and satellite data.
  • Ability to influence technical direction, processes, and product development within a growing organization.
  • Collaboration with a diverse international team across engineering, product, design, and platform functions.
  • Exposure to cutting-edge machine learning, geospatial technologies, and real-world applications.
  • Inclusive culture focused on solving meaningful problems through technology.
  • Opportunity for professional growth in a mission-driven environment.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#J-18808-Ljbffr