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Remote Machine Learning Engineer Jobs in Toledo, OH

Palantir Data Engineer

Perrysburg, OH · On-site +1

$107K - $129K/yr

Palantir Foundry Engineer #0910 Perrysburg, OH 43551 / Hybrid-Remote Long-term ***PLEASE DO NOT APPLY*** if you do not have any PALANTIR FOUNDRY experience. AND **NO Corp-Corp** Description: We are ...

Architect (Remote)

Maumee, OH · Remote

$96K - $135K/yr

ARCHITECT ABOUT US Matrix Technologies, Inc. has been a leading provider of engineering, automation ... Mentor other architects and designers to facilitate a learning experience for subordinate personnel.

Remote Machine Learning Engineer information

See Toledo, OH salary details

$31K

$126.7K

$190.3K

How much do remote machine learning engineer jobs pay per year?

As of Jul 18, 2026, the average yearly pay for remote machine learning engineer in Toledo, OH is $126,658.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $152,500.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually. High compensation often reflects expertise, leadership roles, or working in competitive industries such as tech or finance, especially in organizations valuing AI development.

What are some typical challenges faced by Remote Machine Learning Engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role is unlikely to be fully replaced by AI itself. Instead, AI tools can augment their work by automating routine tasks, allowing MLEs to focus on complex problem-solving, model optimization, and system integration. Continuous learning and expertise in programming, data handling, and model evaluation remain essential for MLEs in an evolving AI landscape.

What are the key skills and qualifications needed to thrive in the Remote Machine Learning Engineer position, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a Remote Machine Learning Engineer job?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

Can ML engineers work remotely?

Yes, many machine learning engineers work remotely, especially in roles that involve programming, data analysis, and model development using tools like Python, TensorFlow, or PyTorch. Remote work arrangements depend on the employer's policies and the specific project requirements, but it is common in the tech industry for ML engineers to work from home or other locations.
What are the most commonly searched types of Machine Learning Engineer jobs in Toledo, OH? The most popular types of Machine Learning Engineer jobs in Toledo, OH are:
What are popular job titles related to Remote Machine Learning Engineer jobs in Toledo, OH? For Remote Machine Learning Engineer jobs in Toledo, OH, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Engineer jobs in Toledo, OH look for? The top searched job categories for Remote Machine Learning Engineer jobs in Toledo, OH are:
What cities near Toledo, OH are hiring for Remote Machine Learning Engineer jobs? Cities near Toledo, OH with the most Remote Machine Learning Engineer job openings:
Infographic showing various Remote Machine Learning Engineer job openings in Toledo, OH as of July 2026, with employment types broken down into 86% Full Time, 10% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $126,658 per year, or $60.9 per hour.
Development Engineer (AI-Augmented Scientific Modeling)

Development Engineer (AI-Augmented Scientific Modeling)

First Solar

Perrysburg, OH • On-site, Remote

Full-time

Posted 11 days ago


First Solar rating

6.8

Company rating: 6.8 out of 10

Based on 73 frontline employees who took The Breakroom Quiz

424th of 528 rated manufacturers


Job description

First Solar reserves the right to offer you a role most applicable to your experience and skillset. 

Basic Job Functions:

First Solar is seeking a self-driven computational scientist, scientific modeling engineer, applied physicist, or AI-augmented research engineer to help accelerate scientific learning and R&D decision-making. The role combines physical reasoning, computation, data analysis, scientific software, and modern AI-assisted workflows to turn complex observations into practical insight.

This role sits at the intersection of scientific modeling, AI-assisted research workflows, data science, simulation, uncertainty analysis, and engineering decision support. The candidate will develop models, software tools, and analytical workflows that help transform scientific information and experimental results into practical engineering insight.

Education/Experience:

  • Bachelor's degree and 10 years of experience, Master's degree and 8 years of experience, or Ph.D. (strongly preferred) and 5 years of experience in Engineering (Chemical, Electrical, Mechanical, or Computational Science and Engineering) or a related technical field (e.g., Applied Mathematics, Scientific Computing, Physics, Materials Science, Astronomy/Astrophysics, Computational Chemistry, or Computational Biology).

  • Relevant experience must include applying computational, physical, statistical, data-driven, or AI-enabled methods to scientific or engineering challenges.

  • Alternatively, candidates with 2 years of experience as a Development Engineer II at First Solar will be considered.

  • Helpful, but not necessary experience:

    • Experience creating models, software tools, or analytical workflows that influenced experimental decisions, process improvements, engineering decisions, or scientific strategy.

    • Experience building computational pipelines for complex experimental or observational data from microscopy, spectroscopy, scattering measurements, tomography, reliability testing, manufacturing systems, or field-performance monitoring.

    • Experience modeling one or more of the following: transport, diffusion, reaction kinetics, degradation, defect physics, semiconductor behavior, electrochemical systems, materials evolution, or coupled process-structure-property relationships.

    • Familiarity with materials science, photovoltaics, semiconductor devices, thin films, defect chemistry, energy materials, manufacturing process data, or field-performance modeling.

Required Skills/Competencies:

  • Strong written and verbal English communication skills, with the ability to participate effectively in cross-functional technical teams.

  • Experience using modern AI tools and integrating AI-assisted methods into scientific, engineering, or research workflows to accelerate modeling, simulation, software development, literature synthesis, data analysis, or technical decision-making.

  • Demonstrated ability to independently learn new scientific, computational, or analytical methods and apply them to unfamiliar technical problems.

  • Ability to work effectively in ambiguous research environments where the correct model, mechanism, or interpretation is not known in advance.

  • Candidates should demonstrate strength in the following areas:
    • Machine learning, AI-assisted scientific workflows, surrogate modeling, or simulation acceleration.
    • Scientific modeling of physical, chemical, materials, device, or engineering systems.
    • Data analysis, inference, uncertainty assessment, optimization, or model calibration.
    • Scientific software development in Python, Julia, C++, MATLAB, C#, or similar environments.
    • Integration of models and algorithms with experimental, operational, reliability, manufacturing, or field data.
    • Ability to connect scientific understanding with practical engineering decisions.
    • Evidence of scientific curiosity, creativity, intellectual independence, and ability to challenge assumptions constructively.

Essential Responsibilities:

  • Develop and apply machine-learning, generative AI, and physics-informed modeling approaches to explore complex structure-property-performance relationships, identify promising design directions, and accelerate scientific understanding of material systems.

  • Evaluate and apply AI-assisted tools and emerging computational methods that meaningfully improve scientific productivity, model development, data analysis, simulation workflows, or engineering decision quality.

  • Translate physical hypotheses, experimental observations, and engineering questions into scientific models, surrogate models, decision-support tools, and AI-enhanced analytical workflows that help researchers understand complex systems, evaluate competing hypotheses, prioritize opportunities, and guide R&D decisions.

  • Implement scientific models and analysis workflows as reusable computational tools with attention to robustness, computational efficiency, documentation, and reproducibility.

  • Identify knowledge gaps, critical uncertainties, and high-value learning opportunities across research programs, to maximize information gained from experiments and simulations.

  • Use experimental data to support model calibration, parameter estimation, uncertainty assessment, sensitivity analysis, and model validation.

  • Work closely with process development, characterization, reliability, device physics, and other technical teams to improve scientific learning cycles, accelerate problem-solving, and convert research insights into practical engineering actions. 

  • Communicate modeling assumptions, limitations, validation results, uncertainty, and technical conclusions clearly to both specialist and non-specialist audiences.

Reporting Relationships:

  • Report to Fellow, Advanced Research.
  • This position will not have direct reports.

Travel:

  • 0% - 5% (On occasion/as needed for training, etc.)

Estimated Salary Range:

  • $80,700 - $135,000 Annually

Physical Requirements:

All positions in our office require interaction with people and technology while either standing or sitting. To best service our customers, internal and external, all associates must be able to communicate face-to-face and on the phone with or without reasonable accommodation. First Solar is committed to compliance with its obligations under all applicable state and federal laws prohibiting employment discrimination. In keeping with this commitment, it attempts to reasonably accommodate applicants and employees in accordance with the requirements of the disability discrimination laws. It also invites individuals with disabilities to participate in a good faith, interactive process to identify reasonable accommodations that can be made without imposing an undue hardship.

Potential candidates will meet the education and experience requirements provided on the above job description and excel in completing the listed responsibilities for this role. All candidates receiving an offer of employment must successfully complete a background check and any other tests that may be required.      

Equal Opportunity Employer Statement: First Solar is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.


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