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Hourly Remote Machine Learning Engineer Jobs in Jordan, MN

QA Engineer - AI Trainer

Minneapolis, MN ยท Remote

$50 - $100/hr

... full-stack, machine learning, and other engineers -- who are driving real-world impact in AI ... Projects are paid hourly starting at $50-100+/hr, with bonus rates available on some projects ...

Remote micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

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Hourly Remote Machine Learning Engineer information

See Jordan, MN salary details

$26.2K

$43.8K

$90.5K

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

As of Jul 10, 2026, the average yearly pay for hourly remote machine learning engineer in Jordan, MN is $43,817.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,400.00 and $47,300.00 per year, depending on experience, location, and employer.

What are some common challenges faced by hourly remote machine learning engineers, and how can they be addressed?

Hourly remote machine learning engineers often encounter challenges such as managing time effectively across multiple projects, ensuring clear communication with distributed teams, and accessing necessary data or computing resources remotely. Building strong routines for regular check-ins and using collaborative tools can help maintain alignment with project goals. Additionally, proactively clarifying expectations and deliverables with clients or team leads can minimize misunderstandings and improve productivity in a remote, hourly environment.

What does an Hourly Remote Machine Learning Engineer do?

An Hourly Remote Machine Learning Engineer is a professional who develops and implements machine learning models and algorithms for clients or employers on an hourly contract basis, all while working from a remote location. Their responsibilities typically include data preprocessing, model selection, training, testing, and deployment. They collaborate with teams via online tools, manage their own schedules, and deliver results according to project requirements. This role allows for flexibility and the opportunity to work on diverse projects across different industries.

What are the key skills and qualifications needed to thrive as an Hourly Remote Machine Learning Engineer, and why are they important?

To thrive as an Hourly Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and experience with data preprocessing, typically supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (e.g., AWS, GCP), and version control systems like Git is essential. Excellent time management, self-motivation, and clear communication skills help you collaborate effectively across distributed teams and manage project-based work. These skills and qualities are vital for delivering high-quality results independently, meeting deadlines, and adapting to the dynamic needs of remote projects.
What cities near Jordan, MN are hiring for Hourly Remote Machine Learning Engineer jobs? Cities near Jordan, MN with the most Hourly Remote Machine Learning Engineer job openings:
Infographic showing various Hourly Remote Machine Learning Engineer job openings in Jordan, MN as of July 2026, with employment types broken down into 1% Locum Tenens, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $43,817 per year, or $21.1 per hour.
Data Scientist (AI, Big Data, SQL, Python) - W2 Only - REMOTE

Data Scientist (AI, Big Data, SQL, Python) - W2 Only - REMOTE

Resource Point LLC

Minneapolis, MN โ€ข Remote

Contractor

Re-posted 17 days ago


Job description

Job Title: Data Scientist (AI, Big Data, SQL, Python) - W2 Only - REMOTE

Location: Minneapolis, MN

Duration: 12+ Months

Description:
Our audit and governance functions require a centralized data leader who can:

  • Architect scalable, secure, compliant data pipelines
  • Translate complex datasets into actionable insights for regulatory and operational decisions
  • Build intuitive, low-maintenance tools that empower non-technical users across the PA experience

Responsibilities:

  • Data Collection & Cleaning - They gather data from various sources and clean it to ensure it's usableโ€”removing errors, filling in missing values, and standardizing formats.
  • Exploratory Data Analysis (EDA) - They explore the data to understand patterns, trends, and relationships using statistical techniques and visualizations.
  • Model Building - They build predictive models using machine learning algorithms to forecast outcomes or classify data.
  • Interpretation & Communication - They translate complex results into actionable insights and communicate them to stakeholders through reports, dashboards, or presentations.
  • Deployment & Monitoring - In some cases, they help deploy models into production systems and monitor their performance over time.

Ideal Background:ย 

  • Healthcare specific background would be helpful.
  • But candidate must be experienced in elements of statistics, computer science, and domain expertise to help organizations make data-driven decisions.
  • As well as, build and maintain artificial intelligence (AI) driven platforms/solutions.

Required Skills:

  • Programming: Python, R, SQL
  • Statistics & Mathematics
  • Machine Learning & AI
  • Data Visualization: Tools like Tableau, Power BI, or libraries like Matplotlib and Seaborn
  • Big Data Tools: Spark, Hadoop (for large-scale data)

Preferred:

  • Advanced SQL and Python for analytics, ETL, and automation
  • Data modeling, warehousing, and pipeline orchestration (cloud, native stack)
  • Dashboarding (Power BI; Streamlit or similar) and reproducible analytics (versioning, CI/CD preferred)
  • Healthcare data familiarity (claims, PA & appeals, pharmacy) and regulatory contexts (CMS, NCQA, URAC, ERISA, state rules)
  • Data security, privacy, and compliance best practices.