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Weekend Machine Learning Software Engineer Jobs in Staunton, VA

Actalent

Project Engineer

Lyndhurst, VA

$120K - $160K/yr

Provide weekend and evening support as needed for field construction work. Essential Skills ... Proficiency in project management software and familiarity with CAD and engineering drawings.

M.C. Dean, Inc

Control Engineer 1

Harrisonburg, VA · On-site

$68K - $85K/yr

... machinery, and processes. Control Engineers work in various applications including industrial ... Perform hardware / software upgrades and replacements on existing systems Qualifications Education ...

E-N Computers

Level 3 Engineer

Waynesboro, VA · On-site

Support hardware/software installations and maintain documentation * Ensure compliance with ... Opportunities for growth and learning * Regional travel and hands-on projects Job Type: FULL TIME, ...

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Weekend Machine Learning Software Engineer information

See Staunton, VA salary details

$62.4K

$145.1K

$202.1K

How much do weekend machine learning software engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for weekend machine learning software engineer in Staunton, VA is $145,059.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,000.00 and $170,100.00 per year, depending on experience, location, and employer.

What is a weekend machine learning software engineer?

A Weekend Machine Learning Software Engineer is a professional who specializes in developing and deploying machine learning models and software systems, but works primarily on weekends. These engineers often collaborate remotely or part-time, contributing to machine learning projects such as model training, data preprocessing, or integration into applications. The role typically requires strong programming skills, experience with machine learning frameworks, and the ability to work independently. Weekend positions may appeal to individuals seeking flexible schedules or supplemental income, while still engaging in advanced technical work.

What are the typical responsibilities and collaboration expectations for a weekend machine learning software engineer?

As a Weekend Machine Learning Software Engineer, you’ll often focus on addressing project backlogs, refining models, and supporting critical deployments during off-peak hours. You’ll typically collaborate remotely with data scientists, product managers, and other engineers through asynchronous communication or scheduled virtual check-ins. The role requires a high degree of independence and strong documentation skills, as well as the ability to quickly troubleshoot and implement solutions with limited direct supervision. This position is ideal for those who are self-motivated and enjoy contributing to core projects outside the standard workweek.

What are the key skills and qualifications needed to thrive as a weekend machine learning software engineer, and why are they important?

To thrive as a Weekend Machine Learning Software Engineer, you need a solid background in computer science, programming (Python, Java, or C++), and applied mathematics, supported by experience with machine learning algorithms. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is typically required. Strong problem-solving skills, effective time management, and the ability to work independently are vital soft skills in this role. These competencies are essential for efficiently delivering robust machine learning solutions during limited weekend hours and collaborating remotely with teams.

What is the difference between Weekend Machine Learning Software Engineer vs Part-Time Data Scientist?

AspectWeekend Machine Learning Software EngineerPart-Time Data Scientist
CredentialsBachelor's or higher in CS, ML, or related fields; experience with ML frameworksBachelor's or higher in Data Science, Statistics, or related fields; analytical skills
Work EnvironmentTech companies, startups, or research labs; project-based tasksResearch institutions, consulting firms, or corporate analytics teams
Usage in IndustryDeveloping ML models, algorithms, and software solutionsData analysis, modeling, and insights generation

The Weekend Machine Learning Software Engineer primarily focuses on developing and implementing machine learning models during weekends, often in a software engineering context. In contrast, a Part-Time Data Scientist emphasizes analyzing data, building statistical models, and deriving insights, often with a broader focus on data analysis rather than software development. Both roles may overlap in skills but differ in their core responsibilities and work environments.

Weekend Machine Learning Software Engineer jobs near you

Research Scientist

Charlottesville, VA • On-site

University of Virginia
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about University of Virginiaexternal

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

University Of Virginia rating

7.9

Company rating: 7.9 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

Job description

Job Summary:
The University of Virginia is a highly regarded public institution known for its commitment to academic excellence, innovation, and service. They are seeking a Research Scientist with expertise in Large Language Models (LLMs) to collaborate with researchers across disciplines, applying LLMs and AI techniques to diverse datasets to enable innovative research outcomes.
Responsibilities:
• Collaborate with researchers to understand datasets and analytical requirements
• Perform data preprocessing and analysis to identify appropriate deep learning and LLM approaches
• Select, fine-tune, and apply LLMs and AI models to complex research problems
• Optimize LLM performance on HPC systems, including parallel implementations
• Manage AI-based research projects to ensure timely delivery and scientific rigor
• Prepare technical reports, presentations, and research outputs
• Develop and deliver training sessions and workshops on LLMs for the UVA community
• Partner with the DAC team to share programming techniques and best practices
Qualifications:
Required:
• Advanced degree (Master’s or higher)
• At least 2 years of relevant work experience
• Proficiency in Python programming
• Demonstrated expertise in AI systems and machine learning algorithms
• Strong analytical and problem-solving abilities
• Excellent written and verbal communication skills
• Ability to collaborate with researchers across diverse disciplines
• Strong relationship-building skills with technical and non-technical stakeholders
• U.S. citizenship or permanent residency required due to access to high-security data environments
• Bachelor’s Degree required
• 3+ years relevant experience required
• Background check required
• This position will not sponsor applicants requiring a visa
Preferred:
• PhD in Computer Science, Electrical Engineering, Data Science, or related field
• 3+ years of academic or applied research experience
• Deep understanding of transformer architectures (attention, tokenization, embeddings, positional encoding, scaling)
• Experience with fine-tuning techniques (supervised fine-tuning, instruction tuning, RLHF, domain adaptation)
• Proficiency with AI frameworks such as PyTorch, TensorFlow, and Hugging Face
• Experience with LLM evaluation and benchmarking methodologies
• Familiarity with generative or probabilistic modeling
• Understanding of LLM risks such as hallucinations and bias, and responsible AI practices
Company:
The University of Virginia was founded in 1819 as the model for modern universities that has since been emulated all over the world. Founded in 1819, the company is headquartered in Charlottesville, USA, with a team of 10001+ employees. The company is currently Late Stage.

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About University of Virginia

Sourced by ZipRecruiter

The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819

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