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Work From Home Data Scientist Machine Learning Jobs in Seattle, WA

Backed by $1B from Greenpoint Partners, we're scaling and building the most valuable logistics ... Build and improve the continuous learning pipeline so new models ship weekly with minimal manual ...

Your Impact We are seeking a highly skilled and innovative Computer Vision and Machine Learning ... from multimodal data sources. * Design and implement efficient and scalable MLLM models for ...

Senior Research Scientist, Perception

Kirkland, WA · On-site +1

$112K - $142K/yr

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing ... Develop and maintain scalable data pipelines for Training & Eval to process data from multiple ...

Senior Research Scientist, Perception

Kirkland, WA · On-site +1

$112K - $142K/yr

The mission of the Waymo AI Foundations team is to develop machine learning solutions addressing ... Develop and maintain scalable data pipelines for Training & Eval to process data from multiple ...

Work from Home - Sales Associate

Tacoma, WA · On-site +1

$15.25 - $20.75/hr

... working from home • Ability to prioritize and multitask • Positions do require applicant to have a Life Insurance license - currently active license, or willing to get a license

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Showing results 41-60

Work From Home Data Scientist Machine Learning information

See Seattle, WA salary details

$42.7K

$139.7K

$223.6K

How much do work from home data scientist machine learning jobs pay per year?

As of Sep 1, 2026, the average yearly pay for work from home data scientist machine learning in Seattle, WA is $139,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,100.00 and $154,800.00 per year, depending on experience, location, and employer.

What is a work from home data scientist machine learning?

A Work From Home Data Scientist specializing in Machine Learning is a professional who analyzes data and builds predictive models using machine learning techniques, while working remotely. Their responsibilities include collecting, cleaning, and interpreting large datasets, creating algorithms, and communicating findings to help organizations make data-driven decisions. They often use programming languages like Python or R, and collaborate with teams through digital tools. This role allows for flexibility in location and often requires strong self-motivation and communication skills.

What are the key skills and qualifications needed to thrive as a work from home data scientist machine learning?

To thrive as a Work From Home Data Scientist in Machine Learning, you need a strong background in statistics, programming (Python or R), and experience with machine learning algorithms, typically supported by a relevant degree in computer science, mathematics, or a related field. Proficiency with tools like TensorFlow, scikit-learn, SQL, and cloud platforms such as AWS or Azure, as well as relevant certifications, is highly valued. Strong problem-solving, self-motivation, and effective remote communication skills set outstanding professionals apart. These skills are crucial for designing robust models, collaborating across remote teams, and delivering actionable insights to drive business decisions.

How does working remotely as a data scientist specializing in machine learning affect team collaboration and project workflow?

As a remote Data Scientist focused on Machine Learning, collaboration is often facilitated through digital communication tools like Slack, Zoom, and version control platforms such as GitHub. Project workflows are typically structured using agile methodologies, with regular virtual stand-ups and sprint reviews to ensure alignment. While remote work offers flexibility, it also requires proactive communication to stay updated on evolving project goals and to coordinate effectively with data engineers, product managers, and other stakeholders. Building strong documentation habits and being responsive during core working hours can help overcome common challenges related to time zone differences or asynchronous work.

What is the difference between Work From Home Data Scientist Machine Learning vs Work From Home Data Analyst?

AspectWork From Home Data Scientist Machine LearningWork From Home Data Analyst
Required SkillsProgramming (Python, R), Machine Learning, Statistical AnalysisData Visualization, Basic Statistical Skills, Excel
CertificationsCertified Data Scientist, Machine Learning CertificationsNone typically required, but certifications like Microsoft Data Analyst are common
Work EnvironmentRemote, collaborative teams, research-focused
Industry UsageTech, Finance, Healthcare, E-commerce

Work From Home Data Scientist Machine Learning roles focus on developing predictive models and advanced algorithms, requiring programming and machine learning expertise. In contrast, Work From Home Data Analyst positions emphasize data interpretation, reporting, and visualization. Both roles are remote-friendly and industry-relevant, but differ in technical depth and scope.

What cities near Seattle, WA are hiring for Work From Home Data Scientist Machine Learning jobs?

Cities near Seattle, WA with the most Work From Home Data Scientist Machine Learning job openings:

Machine Learning Data Engineer

Outpost

Seattle, WA • Remote

$130K - $160K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago


Job description

About Us:

Outpost is building the backbone of freight. We’re reinventing how supply chain infrastructure works in America with carrier agnostic truck terminals. As a vertically integrated real estate, operations, and technology company, we acquire and operate mission-critical real estate across the country to serve the largest logistics providers in the world. Backed by $1B from Greenpoint Partners, we’re scaling and building the most valuable logistics network in the country.

We thrive on accountability, integrity, and a shared drive to raise the bar. If you’re excited to reshape the industry alongside a high-performance team with a championship mindset that executes relentlessly, welcome aboard.

Role Summary:

Our platform combines AI-powered gate automation, computer vision, and operational software to help logistics operators run smarter, faster facilities. We're a small, high-conviction team shipping real software that ends up in real yards, at real gates, moving real freight; and we're growing fast, with revenue set to grow 10X over the next 18 months.

As we onboard more customers, our computer vision system sees more camera layouts, identifier types, and edge cases than ever. We need someone to own accuracy end-to-end: measuring it, understanding why we get it wrong, and turning that into the labeled data that makes our models better. Today that's mostly measurement and curation. Once the pipeline matures and moves into maintenance mode, we expect this role to also contribute fixes to the product itself, not just flag issues for others to resolve.

Key Responsibilities:

  • Own tracking and reporting of CV accuracy metrics, per customer and per identifier type.

  • Investigate misclassifications and false negatives, categorize root causes, and identify patterns across customers and yards.

  • Curate, label, and prioritize datasets for model retraining, partnering closely with our ML and CV engineers.

  • Build and improve the continuous learning pipeline so new models ship weekly with minimal manual engineering effort.

  • Define functional acceptance criteria for CV accuracy per customer and track progress against them.

  • Translate accuracy findings into decisions the engineering team and customer-facing stakeholders can act on.

  • As the pipeline matures, expect to move from flagging issues to fixing them directly; building the labeling/preprocessing tooling, running retraining jobs, and owning fixes for the error patterns you find, not just reporting them.

What You Can Expect:

  • Direct ownership over the metric that decides whether our product works in the real world.

  • A small team that moves fast, argues in good faith, and trusts engineers to make decisions.

  • Real influence on what the ML team builds next; your findings drive the roadmap, not the other way around.

  • Problems grounded in the physical world: gates, cameras, trucks, and yards.

Qualifications:

  • 3+ years in a data quality, ML data engineering or applied ML role.

  • Experience working with computer vision or object detection systems in production.

  • Comfortable writing Python for data analysis, pipeline automation, and dataset tooling.

  • Strong analytical rigor, comfortable digging into large volumes of imagery/data to find patterns, not just running a script and reporting a number.

  • Experience with dataset annotation/labeling tools and workflows (Roboflow, Labelbox, CVAT, or similar).

  • Strong communication skills.

Preferred Qualifications:

  • Experience with continuous learning or active learning pipelines for production ML systems.

  • Familiarity with OCR systems and identifier recognition (plates, container numbers, etc.).

  • Experience partnering with customer success or support teams on quality metrics.

  • Background in QA/test engineering for ML systems.

  • Experience with Roboflow specifically.

Our Stack:

Python · Roboflow · VLM/OCR pipelines · GCP (GCS) · PostgreSQL · Snowflake · Node.js/TypeScript

 

Benefits:

  • Title Commensurate with Experience

  • Comprehensive Benefits Package including Health, Dental, and Vision Insurance

  • 401(k) Retirement Plan Matching

  • 18 Paid Holidays

  • Unlimited PTO

  • Friday Team Lunches

  • Base salary range: $130,000 – $160,000 annually, depending on experience and qualifications. Total compensation includes a discretionary bonus; a complete compensation and benefits summary will be provided during the interview process.

Outpost is an Equal Opportunity Employer and Prohibits Discrimination of Any Kind.