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Machine Learning Biology Jobs in Seattle, WA (NOW HIRING)

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Work closely with agronomists and farmers to understand crop biology and translate domain knowledge ...

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions ... Work closely with agronomists and farmers to understand crop biology and translate domain knowledge ...

About the Role We are searching for a curious and motivated AI Research Scientist to invent and advance machine learning methods for biological discovery at scale. Rather than primarily applying ...

About the Role We are searching for a curious and motivated AI Research Scientist to invent and advance machine learning methods for biological discovery at scale. Rather than primarily applying ...

... such as biology, cancer research, neuroscience, social science, etc. • Designing, building, and training machine learning or language models for agentic workflows. • Bridging the gap between ...

... such as biology, cancer research, neuroscience, social science, etc. • Designing, building, and training machine learning or language models for agentic workflows. • Bridging the gap between ...

... such as biology, cancer research, neuroscience, social science, etc. • Designing, building, and training machine learning or language models for agentic workflows. • Bridging the gap between ...

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Showing results 1-20

Machine Learning Biology information

See Seattle, WA salary details

$26.2K

$59.4K

$84.8K

How much do machine learning biology jobs pay per year?

As of Aug 4, 2026, the average yearly pay for machine learning biology in Seattle, WA is $59,393.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,100.00 and $68,800.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in machine learning biology?

Professionals in Machine Learning Biology often deal with challenges such as handling large and complex biological datasets, integrating heterogeneous data types (like genomics, proteomics, or imaging), and addressing the noise and variability inherent in biological data. Interpreting results in a biologically meaningful way and ensuring reproducibility of models can also be complex, requiring close collaboration with experimental scientists. Many teams are cross-functional, so frequent communication with biologists, clinicians, and software engineers is important for project success. While these challenges can be demanding, they also offer opportunities for innovation and significant contributions to scientific discovery or medical advances.

What is a machine learning biology?

A Machine Learning Biology job involves applying machine learning techniques to analyze biological data, such as genomic sequences, protein structures, or medical images. Professionals in this field develop algorithms to identify patterns, make predictions, and derive insights that can advance research in drug discovery, personalized medicine, and biotechnology. These roles typically require expertise in biology, data science, and programming, often using tools like Python, TensorFlow, or scikit-learn.

What are the key skills and qualifications needed to thrive in machine learning biology?

To thrive as a Machine Learning Biology professional, you need expertise in both computational methods (especially machine learning and data science) and a solid understanding of biological sciences, typically supported by an advanced degree in bioinformatics, computational biology, or a related field. Familiarity with programming languages like Python or R, experience using machine learning frameworks (such as TensorFlow or scikit-learn), and working with biological databases are highly valued. Strong analytical thinking, problem-solving abilities, and effective interdisciplinary communication are key soft skills for this position. These competencies are vital for translating complex biological data into actionable insights and advancing research or product development in biotechnology and life sciences.

What are the most commonly searched types of Machine Learning Biology jobs in Seattle, WA? The most popular types of Machine Learning Biology jobs in Seattle, WA are:
What are popular job titles related to Machine Learning Biology jobs in Seattle, WA? For Machine Learning Biology jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Biology jobs in Seattle, WA look for? The top searched job categories for Machine Learning Biology jobs in Seattle, WA are:
Infographic showing various Machine Learning Biology job openings in Seattle, WA as of July 2026, with employment types broken down into 73% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $59,393 per year, or $28.6 per hour.

Machine Learning Engineer

Orchard Robotics

Seattle, WA • On-site

$135K - $210K/yr

Full-time

Medical, Dental, Vision

Re-posted 23 days ago


Job description

Orchard Robotics is a Series A startup backed by top VCs like Quiet Capital, Shine Capital, and General Catalyst. We're securing America’s food supply by building the AI farmer that automates our nation’s farms. We've raised over $25M in pursuit of our mission to help farmers farm more profitably and sustainably than ever before.

What We Do:

We start by building AI-powered camera systems that collect the most valuable data for farmers, telling them everything about what is growing on their millions of trees, vines, and plants, across thousands of acres of farmland.

Our state-of-the-art AI analyzes every one of the billions of fruit across a farm. We provide accurate yield estimates, fruit counts, size projections, disease detection, inventories, bloom maps, and more! All this data lives in our cloud platform, FruitScope OS, that we've developed from the ground up to enable farmers to manage their crop with precision.

Today, our technology is trusted by some of the largest farms in the nation. We are growing fast, and have the industry-leading product. Farmers use our software every day to make critical decisions and run more efficient, profitable operations.

The Role:

In order to analyze billions of fruit on farms all year long, our advanced, tractor-mounted camera systems have to know a.) precisely where they are, and b.) everything about the fruit they are seeing.

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems, relating to training edge ML models on massive amounts of real-world farm image data collected by our camera systems.

About the role: 

  • Full-time, in-person role at our San Francisco or Seattle office.

  • As an early engineer, you'll receive generous equity compensation

  • Comprehensive Health, Vision, and Dental coverage, and we cover 100% of the premium

  • We move fast, and sometimes this means staying late or working weekends 

  • Our team is close-knit & highly driven, you’ll work directly with our CEO and entire team

  • We’re deeply motivated by the impact we’re making – every line of code written or new system built means less food that goes to waste, and more people who are fed.

What you’ll do:

  • Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms.

  • Develop and deploy infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices.

  • Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance.

  • Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems.

  • Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems.

  • Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features.

  • Be a generalist, supporting different parts of our software stack as needed.

What makes you a good fit:

  • 2+ years of real-world, industry experience building production-grade data pipelines and ML infrastructure.

  • Proficiency in Python and experience with ML frameworks (e.g., PyTorch).

  • Strong experience with data engineering tools (e.g., Pandas, SQL, MLFlow, WandB).

  • Familiarity with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes).

  • Experience working with massive amounts of real-world training data.

  • Familiarity with MLops software and data engineering to ensure consistent deployment of ML models.

  • Ability to work independently, learn quickly, and operate in a dynamic environment

  • Enthusiasm for taking on multiple roles and responsibilities as our company grows.

Bonus Points:

  • Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson

  • Experience prototyping, evaluating, or deploying new ML/CV models on the edge.

If you're looking to help make a positive impact in the world by building the future of farming, come join us!

Compensation Range: $135K - $210K