1

Contract Machine Learning Data Scientist Jobs (NOW HIRING)

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, data mining, advanced statistical analysis, advanced mathematical ...

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, data mining, advanced statistical analysis, advanced mathematical ...

Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming, data mining, advanced statistical analysis, advanced mathematical ...

A Data Scientist represents an effective arbiter of strong technical knowledge and clear ... May use machine learning and statistical approaches based on the analysis of the dataset. May ...

Data Scientist

Chantilly, VA · On-site

$165K - $210K/yr

A Data Scientist represents an effective arbiter of strong technical knowledge and clear ... May use machine learning and statistical approaches based on the analysis of the dataset. May ...

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

We hire for careers , not contracts--our work is growing * People-Focused Culture: We value work ... We are seeking talented and motivated Data Scientists with expertise in machine learning ...

next page

Showing results 1-20

Contract Machine Learning Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do contract machine learning data scientist jobs pay per year?

As of Jul 3, 2026, the average yearly pay for contract machine learning data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

How do contract machine learning data scientists typically collaborate with in-house teams during a project?

Contract machine learning data scientists often work closely with in-house data teams, product managers, and engineers to align project goals and deliverables. They frequently participate in virtual meetings, code reviews, and regular progress updates to ensure transparency and seamless integration of their work. Effective communication and documentation are critical, as contractors may need to quickly adapt to the company's workflows and tools. This collaborative environment enables contractors to contribute specialized expertise while staying attuned to the broader objectives of the organization.

What are the key skills and qualifications needed to thrive as a Contract Machine Learning Data Scientist, and why are they important?

To excel as a Contract Machine Learning Data Scientist, you need a strong background in statistics, programming (Python/R), and applied machine learning, typically supported by a relevant degree in computer science, mathematics, or a related field. Familiarity with tools and frameworks such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP, Azure), and version control systems is essential, along with experience deploying models in production. Exceptional problem-solving abilities, communication skills, and adaptability help you translate business needs into actionable data solutions and quickly integrate into new teams. These skills are crucial for delivering high-impact, reliable machine learning solutions on tight project timelines and in diverse organizational environments.

What is the difference between Contract Machine Learning Data Scientist vs Contract Data Scientist?

AspectContract Machine Learning Data ScientistContract Data Scientist
CredentialsTypically requires advanced degrees in data science, machine learning, or related fieldsRequires similar degrees but may have a broader focus on data analysis
Work EnvironmentOften in tech, finance, or healthcare industries focusing on ML projectsVaries across industries, including marketing, finance, and consulting
Employer UsageUsed by companies developing AI/ML solutions or productsEmployed for data analysis, reporting, and strategic insights
Search & Comparison IntentOften searched by those interested in AI/ML-specific rolesMore general, related to data analysis roles

The main difference is that Contract Machine Learning Data Scientists focus on developing and implementing machine learning models, while Contract Data Scientists may handle broader data analysis tasks without necessarily specializing in ML. Both roles require strong analytical skills and relevant credentials, but their project focus and industry applications differ.

What is a Contract Machine Learning Data Scientist?

A Contract Machine Learning Data Scientist is a professional who works on a temporary or project-based basis to build, implement, and optimize machine learning models for organizations. Unlike full-time employees, contract data scientists are hired for specific projects or timeframes and may work independently or as part of a team. Their responsibilities typically include data cleaning, feature engineering, model selection, and communicating insights to stakeholders. Contract roles offer flexibility for both the professional and the employer, often focusing on specialized tasks or filling short-term skill gaps.
More about Contract Machine Learning Data Scientist jobs
What cities are hiring for Contract Machine Learning Data Scientist jobs? Cities with the most Contract Machine Learning Data Scientist job openings:
What states have the most Contract Machine Learning Data Scientist jobs? States with the most job openings for Contract Machine Learning Data Scientist jobs include:
Infographic showing various Contract Machine Learning Data Scientist job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Machine Learning - Data Scientist Lead

Machine Learning - Data Scientist Lead

Apple

Sunnyvale, CA

$181K - $318K/yr

Full-time

Medical, Dental, Retirement

Posted 4 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 666 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

Do you have a passion for computer vision and deep learning? Are you excited by the latest advances in multimodal models? The Video Engineering Data Analytics and Quality group is looking for a technical lead with deep expertise in evaluating machine learning and deep learning models, including foundation models and multimodal systems.
Description
In this role, you will design robust evaluation frameworks, mentor a team of engineers and scientists, and drive alignment across Apple's research, engineering, and product teams. You will combine strong analytical thinking, Python expertise, and a deep understanding of statistical evaluation and data quality. You will also help set the technical direction for how we measure and improve the quality of some of Apple's most exciting AI experiences.","responsibilities":"Lead and mentor a small team of ML evaluation engineers and data scientists, providing technical guidance, feedback, and code reviews.
Define team-level evaluation standards and best practices that other teams across Apple can adopt.
Own the technical roadmap for evaluation infrastructure, from planning through execution.
Onboard and ramp up new team members on tools, datasets, and workflows.
Design and implement scalable evaluation frameworks for machine learning and deep learning models.
Develop robust methodologies to assess the performance of foundation models (such as LLMs and vision-language models) across diverse tasks.
Leverage LLMs as judges to perform subjective and open-ended model evaluations, for example in summarization, reasoning, or multimodal generation tasks.
Create, curate, and manage evaluation datasets and benchmarks.
Drive cross-functional alignment by partnering with product managers, research leads, and engineering managers to prioritize evaluation goals.
Collaborate with ML engineers, data scientists, and ML infrastructure engineers to deliver great user experiences.
Communicate findings clearly through dashboards, presentations, and technical documentation.
Influence without authority across teams with different goals and priorities.
Conduct failure analysis and uncover edge cases to improve model robustness.
Contribute to internal tools and infrastructure to automate and scale evaluation processes.
Write clear technical reports and present findings to both technical and non-technical audiences.
Preferred Qualifications
M.S. or Ph.D. in Computer Science, Statistics, Machine Learning, or a related field.
Prior experience managing or tech-leading a team of two or more engineers or scientists.
Experience with open-source evaluation tools such as OpenEval, ELO-based ranking, or LLM-as-a-Judge frameworks.
Familiarity with prompt engineering, few-shot, or zero-shot evaluation techniques.
Experience evaluating generative models, such as text or image generation systems.
Prior contributions to ML benchmarks or public evaluations.
Comfort with giving and receiving feedback in a collaborative, fast-moving environment.
Strong communication and documentation skills, with the ability to write technical reports and present to non-technical audiences.
Minimum Qualifications
BS and a minimum of 10 years relevant industry experience.
4+ years of industry or academic experience in machine learning or data science.
2+ years of experience leading technical projects or mentoring junior engineers or scientists.
Strong experience evaluating supervised, unsupervised, and deep learning models.
Hands-on experience with LLMs (such as GPT, Claude, or PaLM) and using them as scoring or judging mechanisms.
Familiarity with multimodal models (such as image + text or video + audio) and their evaluation challenges.
Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.
Solid understanding of statistical testing, sampling, confidence intervals, and metrics such as precision/recall, BLEU, ROUGE, and FID.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976