2

Remote Machine Learning Engineer Jobs in Rock Island, IL

Remote Job Overview We are seeking experienced Senior Software Engineers with strong open-source profiles to create and evaluate challenging software engineering tasks for AI training. You will build ...

New

Software Engineer Job Location: Moline, IL, US Job Type: Permanent Our client is looking for mid-level software engineers experienced in Typescript, ReactJS, Redux, and AWS to work on projects for ...

Sr. Virtual Solutions Engineer

Davenport, IA · On-site +1

$92K - $127K/yr

As a pioneering developer and leading producer of fiber lasers and amplifiers, we are committed to applying light-based technologies in ways that improve life. Our mission is to develop innovative ...

Data Engineer

Moline, IL · On-site +1

$88K - $133K/yr

OVERVIEW We are seeking a highly skilled and motivated Data Engineer responsible for supporting the Credit Union and Data & Analytics with efficient data solutions that are dynamic and automated.

The work model for the role is Remote based out of Florida, USA. This role is contributing to the ... Currently enrolled in a bachelor's or master's degree program in Engineering, Business, Marketing ...

This internship is primarily a remote opportunity. However, if you are located near one of our ... September 27, 2026 Engineering postings close: October 2, 2026 Interviews: Early to mid October ...

Showing results 21-40

Remote Machine Learning Engineer information

See Rock Island, IL salary details

$29.9K

$122.2K

$183.6K

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

As of Sep 13, 2026, the average yearly pay for remote machine learning engineer in Rock Island, IL is $122,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,300.00 and $147,000.00 per year, depending on experience, location, and employer.

What is a remote machine learning engineer?

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.

What are the key skills and qualifications needed to thrive as a remote machine learning engineer?

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 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.

Are remote machine learning engineers still in demand?

Remote machine learning engineers are currently in high demand due to the growth of AI and data-driven technologies across industries. Skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch are highly sought after, and many companies continue to hire for remote roles in this field.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for this role. The position typically involves tasks such as data analysis, model development, and collaboration through online tools, making remote work feasible with strong communication skills and proficiency in programming languages like Python or frameworks like TensorFlow. However, some roles may require occasional on-site meetings or access to specialized hardware.

What job categories do people searching Remote Machine Learning Engineer jobs in Rock Island, IL look for?

The top searched job categories for Remote Machine Learning Engineer jobs in Rock Island, IL are:

What cities near Rock Island, IL are hiring for Remote Machine Learning Engineer jobs?

Cities near Rock Island, IL with the most Remote Machine Learning Engineer job openings:

Infographic showing various Remote Machine Learning Engineer job openings in Rock Island, IL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $122,156 per year, or $58.7 per hour.

GitHub Contributor - Rmote

Illinois City, IL • Remote

$50 - $150/hr

Full-time

Posted 2 days ago

New


Job description

GitHub Contributor – Senior Software Engineer

Role Type: Contractor (~15 hrs/week)
Location: Remote

Job Overview

We are seeking experienced Senior Software Engineers with strong open-source profiles to create and evaluate challenging software engineering tasks for AI training. You will build reproducible environments and reference solutions that test AI models on debugging, feature development, refactoring, and performance optimization.

No prior AI experience is required—your software engineering expertise and open-source contributions are what matter most.

Key Responsibilities
  • Create expert-level software engineering tasks involving bug fixing, feature implementation, refactoring, and optimization.
  • Develop reproducible environments and golden reference solutions for AI evaluation.
  • Work with Python, Java, Rust, C++, Go, and/or TypeScript codebases.
  • Debug complex systems and resolve performance bottlenecks.
  • Implement scalable and maintainable features.
  • Refactor legacy code and improve performance and reliability.
  • Document technical reasoning, solutions, and code decisions.
  • Review and validate technical submissions for quality and accuracy.
Required Skills
  • Python 3
  • Java
  • Rust
  • C++
  • TypeScript
  • Algorithms & Data Structures
  • Bug Fixing
  • Feature Implementation
  • Codebase Refactoring
  • Performance Optimization
Preferred Qualifications
  • Significant experience in one or more listed programming languages.
  • Strong algorithms, data structures, and software engineering fundamentals.
  • Experience debugging complex systems and optimizing performance.
  • Experience working with large codebases and legacy system modernization.
  • Proven open-source contributions on GitHub or GitLab.
  • Experience delivering features from conception through implementation.
  • Strong technical documentation and communication skills.
  • Interest in AI and software engineering evaluation is a plus.
Selection Process
  1. Application and screening questions
  2. ~30-minute AI interview
  3. Technical assessment (if applicable)
  4. Hiring Manager review
Compensation & Availability

Compensation is output-based, with payment per qualifying task. Minimum weekly submission requirements apply.

Selected experts should be ready to begin their first tasks within 24–48 hours of completing onboarding. Roles are typically filled within 48 hours.