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Entry Level Machine Learning Engineer Jobs in Redmond, WA

Orchard Robotics

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 to ML/CV software and infrastructure problems , relating to training edge ML models on massive ...

Apple

AIML - Machine Learning Engineer, MIND

Seattle, WA

$139K - $258K/yr

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the ...

Apple

Staff Machine Learning Engineer

Seattle, WA · On-site

Staff Machine Learning Engineer Join a team at the forefront of ML infrastructure and generative AI, where data and model workflows come together to enable the next generation of intelligent ...

Chewy

Staff Machine Learning Engineer

Bellevue, WA · On-site

$186K - $265K/yr

At Chewy, Sponsored Ads team is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite sponsored ads. As a member to the Sponsored ...

Chewy

Staff Machine Learning Engineer

Bellevue, WA · On-site

$186K - $265K/yr

At Chewy, Sponsored Ads team is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite sponsored ads. As a member to the Sponsored ...

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All JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Redmond, WA

Entry Level Machine Learning Engineer information

See Redmond, WA salary details

$33.6K

$77.7K

$132.2K

How much do entry level machine learning engineer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for entry level machine learning engineer in Redmond, WA is $77,682.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,700.00 and $87,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Redmond, WA? The most popular types of Machine Learning Engineer jobs in Redmond, WA are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Redmond, WA? For Entry Level Machine Learning Engineer jobs in Redmond, WA, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Redmond, WA look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Redmond, WA are:
What cities near Redmond, WA are hiring for Entry Level Machine Learning Engineer jobs? Cities near Redmond, WA with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Redmond, WA as of June 2026, with employment types broken down into 11% Internship, 71% Full Time, 12% Part Time, and 6% Temporary. Highlights an 94% In-person, and 6% Remote job distribution, with an average salary of $77,682 per year, or $37.3 per hour.

Machine Learning Engineer

Orchard Robotics

Seattle, WA • On-site

$135K - $210K/yr

Full-time

Medical, Dental, Vision

Posted 7 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!

Apply