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Weekend Machine Learning Software Engineer Jobs in Ridgefield, CT

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Weekend Machine Learning Software Engineer information

See Ridgefield, CT salary details

$63.2K

$146.9K

$204.7K

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

As of Aug 15, 2026, the average yearly pay for weekend machine learning software engineer in Ridgefield, CT is $146,925.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,500.00 and $172,300.00 per year, depending on experience, location, and employer.

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 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 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.

Machine Learning Engineer

Kforce Technology Staffing

Armonk, NY • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Job description

RESPONSIBILITIES:
Kforce has a client in Armonk, NY that is seeking a Lead Machine Learning Engineer to support a leading Energy and Utilities organization by designing and delivering scalable machine learning solutions that drive operational efficiency and business decision-making. This role will own the end-to-end machine learning architecture, lead the design of predictive models and recommendation engines, and guide models from prototype through production deployment.
Responsibilities:
* Design and own the overall machine learning system architecture and model lifecycle
* Develop scalable predictive models and recommendation engines to support operational and resource planning initiatives
* Lead technical design decisions and mentor small delivery teams throughout the development lifecycle
* Translate business requirements into machine learning solutions and production-ready models
* Partner with data engineers, data scientists, and business stakeholders to deliver high-impact analytics solutions
* Deploy, monitor, and optimize machine learning models using Azure Machine Learning
* Establish best practices for model governance, performance monitoring, and continuous improvement
* Maintain CI/CD workflows, version control, and containerized deployments using GitHub and Docker
REQUIREMENTS:
* 8+ years of experience in Machine Learning Engineering, Data Engineering, or AI solution development
* Proven experience designing enterprise-scale machine learning architectures and deploying production ML solutions
* Strong Python development experience including pandas, scikit-learn, XGBoost/LightGBM, and PyTorch (preferred)
* Advanced SQL skills with experience working in Snowflake
* Hands-on experience with Azure Machine Learning, GitHub, and Docker
* Strong understanding of MLOps, model deployment, monitoring, and lifecycle management
* Experience leading technical teams and delivering enterprise analytics solutions
Preferred Qualifications:
* Experience with optimization algorithms, operations research, or resource planning
* Experience within the Energy and Utilities industry or another regulated environment
* Familiarity with enterprise operational data platforms and utility data ecosystems
* Strong communication skills with the ability to bridge business needs and technical solutions
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
By clicking ?Apply Today? you agree to receive calls, AI-generated calls, text messages or emails from Kforce and its affiliates, and service providers. Note that if you choose to communicate with Kforce via text messaging the frequency may vary, and message and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will always have the right to cease communicating via text by using key words such as STOP.