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Part Time Machine Learning Visa Sponsorship Jobs

... to part-time, non-permanent projects. Ideally, contributors will have: * 5+ years of hands-on ... Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and ...

... to part-time, non-permanent projects. Ideally, contributors will have: * 5+ years of hands-on ... Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and ...

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Part Time Machine Learning Visa Sponsorship information

See salary details

$25.5K

$42.6K

$88K

How much do part time machine learning visa sponsorship jobs pay per year?

As of Jun 9, 2026, the average yearly pay for part time machine learning visa sponsorship in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by part-time machine learning professionals working under visa sponsorship?

Part-time machine learning professionals on visa sponsorship often navigate unique challenges such as balancing strict work-hour limitations with project deadlines and expectations. They may also encounter complexities related to communication and integration with full-time teammates, especially if work schedules differ. Additionally, understanding visa compliance requirements and maintaining eligibility for continued sponsorship can add administrative responsibilities. However, many organizations offer structured onboarding and clear channels for support to help part-time sponsored employees succeed in their roles.

What is a Part Time Machine Learning Visa Sponsorship job?

A Part Time Machine Learning Visa Sponsorship job is a role where an employer hires an individual to work in the field of machine learning on a part-time basis and is willing to sponsor their visa to work legally in the country. These positions are ideal for international candidates who have expertise in machine learning but require visa support. Responsibilities typically include developing, testing, and deploying machine learning models while adhering to the work hour limitations of a part-time position. Sponsorship may depend on the company's policies and local immigration regulations. It's important to check the specific visa type and eligibility requirements before applying.

What are the key skills and qualifications needed to thrive as a Part-Time Machine Learning Engineer, and why are they important?

To thrive as a Part-Time Machine Learning Engineer, you generally need a strong background in mathematics, statistics, programming (often Python), and hands-on experience with machine learning algorithms, usually supported by a relevant degree or coursework. Familiarity with ML frameworks like TensorFlow or PyTorch, version control systems such as Git, and cloud platforms like AWS or GCP is typically required, and certifications can enhance your profile. Strong problem-solving abilities, effective communication, and time management skills are essential soft skills for collaborating on projects and balancing part-time responsibilities. These skills and qualifications are crucial for developing robust machine learning solutions efficiently while meeting project goals and deadlines.

What is the difference between Part Time Machine Learning Visa Sponsorship vs Part Time Data Scientist Visa Sponsorship?

AspectPart Time Machine Learning Visa SponsorshipPart Time Data Scientist Visa Sponsorship
Required CredentialsRelevant degrees in computer science, data science, or related fields; certifications in machine learningDegrees in data science, statistics, or related fields; certifications in data analysis
Work EnvironmentResearch labs, tech companies, startups focusing on AI/ML projectsBusiness analytics, research teams, consulting firms
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, consulting, and tech industries

Both roles require similar educational backgrounds and certifications, often working in tech or research environments. The main difference lies in focus: machine learning roles emphasize developing algorithms, while data scientist roles focus on data analysis and insights. Visa sponsorship options are similar, but job responsibilities and industry applications differ slightly.

More about Part Time Machine Learning Visa Sponsorship jobs
What cities are hiring for Part Time Machine Learning Visa Sponsorship jobs? Cities with the most Part Time Machine Learning Visa Sponsorship job openings:
What are the most commonly searched types of Machine Learning Visa Sponsorship jobs? The most popular types of Machine Learning Visa Sponsorship jobs are:
What states have the most Part Time Machine Learning Visa Sponsorship jobs? States with the most job openings for Part Time Machine Learning Visa Sponsorship jobs include:
What job categories do people searching Part Time Machine Learning Visa Sponsorship jobs look for? The top searched job categories for Part Time Machine Learning Visa Sponsorship jobs are:
Infographic showing various Part Time Machine Learning Visa Sponsorship job openings in the United States as of June 2026, with employment types broken down into 69% Full Time, 8% Part Time, 4% Temporary, and 19% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Sr. Engineer, Machine Learning Operations

Sr. Engineer, Machine Learning Operations

Exact Sciences

San Diego, CA

$209K/yr

Full-time, Part-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Exact Sciences rating

8.5

Company rating: 8.5 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

19th of 103 rated laboratories


Job description

Help us change lives

At Exact Sciences, we’re helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you’re working to help others.

Position Overview

The Sr. Engineer, Machine Learning Operations, with minimal guidance, works independently and with cross‑functional partners—including biostatisticians, bioinformatics scientists, AI scientists, and software engineers—to deploy, operate, and scale machine learning solutions in production for advanced cancer screening and precision oncology applications. The role designs, builds, and maintains robust ML platforms and pipelines that ensure reliability, security, and compliance across the full model lifecycle—from data ingestion, model training, versioning and evaluation, through deployment, monitoring, and continuous improvement. This role serves as a key resource, applying in‑depth practical knowledge of ML Operations, software engineering, and cloud infrastructure to solve complex problems across multiple projects, ensuring AI/ML models are production-ready, observable, and aligned with the company's mission to help eradicate cancer.

Essential Duties

Include, but are not limited to, the following:

  • Designs, implements, and maintains end‑to‑end MLOps pipelines for training, validation, deployment, and monitoring of ML and AI models used in cancer screening and precision oncology solutions.
  • Builds and operates scalable, secure ML infrastructure on cloud and container platforms (e.g., AWS/Azure/GCP, Docker, Kubernetes) to support batch and real‑time inference workloads.
  • Implements CI/CD workflows for ML (data, model, and code), including automated testing, packaging, and promotion of models across development, staging, and production environments.
  • Establishes and manages model and data versioning, experiment tracking, and lineage to ensure reproducibility, auditability, and effective model governance.
  • Develops and maintains monitoring, logging, and alerting for model performance, data quality, drift, and system health, defining and meeting SLOs/SLAs for critical ML services.
  • Collaborates with data scientists, bioinformatics and biostatistics partners, and software/platform engineering teams to translate experimental workflows into production‑grade services integrated into customer‑facing and internal applications.
  • Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
  • Support and comply with the company’s Quality Management System policies and procedures.
  • Maintain regular and reliable attendance.
  • Ability to act with an inclusion mindset and model these behaviors for the organization.
  • Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 90% of a typical working day.
  • Ability to travel 5% of working time away from work location, may include overnight/weekend travel.

Minimum Qualifications

  • Bachelor’s Degree in a field related to essential duties; or Associates Degree and 2 years of relevant experience.; or High School Diploma or General Education Degree (GED) and 4 years of relevant experience.
  • 5 years of relevant job-related experience.
  • Demonstrated experience with Python, at least one major ML framework (e.g., TensorFlow, PyTorch, scikit‑learn), containerization and orchestration technologies (e.g., Docker, Kubernetes), and a major cloud platform (e.g., AWS, Azure, GCP) supporting ML workloads.
  • Demonstrated ability to perform the essential duties of the position with or without accommodation.
  • Applicants must be currently authorized to work in country where work will be performed on a full or part-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time. 

Preferred Qualifications

  • 2+ years of life sciences industry experience working with biological data.
  • 2+ years of industry experience in molecular diagnostics, preferably cancer diagnostics.
  • Expertise in data mining approaches within healthcare settings generating insight from routinely collected healthcare data.
  • Scientific understanding of cancer biology
  • Strong programming ability in Python and experience with at least one major ML framework (e.g., TensorFlow, PyTorch, scikit-learn).
  • Hands-on experience deploying and operating machine learning models in production, including experience with CI/CD pipelines, model packaging, and automated deployment.
#LI-CB1

Salary Range:

National Ranges: $ 123,000.00 - $209,000.00

California Ranges: $152,000.00- $228,000.00

 

The annual base salary shown is a national range for this position on a full-time basis and may differ by hiring location. In addition, this position is bonus eligible.

 

Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits.

Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, please contact us here.

Not ready to apply? Join our Talent Community to stay updated on the latest news and opportunities at Exact Sciences.

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, and any other status protected by applicable local, state, or federal law.

To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub. The documents summarize important details of the law and provide key points that you have a right to know.


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