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Senior Embedded Machine Learning Jobs in Oregon (NOW HIRING)

Nvidia

Senior Machine Learning Engineer, AI Safety

OR · On-site +1

$114K - $156K/yr

NVIDIA is seeking talented Deep Learning Scientists / AI Researchers / Machine Learning Engineers to join our rapidly growing AI Safety and Responsibility efforts for Enterprise Risk Management. In ...

Cresta

Staff Machine Learning Engineer

OR · On-site +1

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team ... Mentor senior engineers, raise the technical bar, and contribute to long-term AI strategy and ...

Agility Robotics

Senior Safety Software Engineer

Salem, OR · On-site +1

$175K - $274K/yr

Partner with our machine learning, hardware, and core software teams to ensure that data pipelines ... Strong understanding of software architecture for embedded * Excellent problem-solving skills and a ...

Embedded Shishya

Senior Data Scientist

Portland, OR · On-site

$166K - $250K/yr

To that end, we are hiring a Machine Learning-focused Data Scientist to support our Risk team. This team is responsible not only for detecting, monitoring, and mitigating both first- and third-party ...

New

Netflix

Machine Learning Scientist (L6) - Live Ads

OR · On-site +1

... senior staff-level scope and impact. Deep knowledge of machine learning, optimization, and data ... analysis techniques. Experience in ad optimization stack, e.g. targeting, ranking, bidding.

Deegit Inc

DSP Algorithms Engineer

Hillsboro, OR · On-site

$155K - $181K/yr

... point embedded software. Creative problem solver, team player Qualifications Proficient in DSP theory, scientific programming, adaptive filtering, machine learning, GMM, clustering and neural ...

Nike

Senior Software Engineer

Beaverton, OR · On-site

$127K - $168K/yr

... machine learning models to support prediction and optimization use cases; operationalize machine learning models as scalable APIs or batch inference services; implement and maintain CI/CD pipelines ...

Instacart

Senior Product Manager, Ads Quality

OR · On-site +1

$126K - $166K/yr

As part of the Ad Product team, you'll sit at the intersection of machine learning, marketplace ... We're looking for a Senior Product Manager to own the systems that drive core auction understanding ...

Hubble Network

Senior Sales Engineer, Embedded & IoT

OR · On-site +1

The role We're hiring a Senior Sales Engineer to be the technical anchor of our sales organization ... High learning agility - you like learning, you're honest about what you don't know yet, and you ...

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All JobsEmbedded Machine Learning JobsSenior Embedded Machine Learning JobsSenior Embedded Machine Learning Jobs in Oregon

Senior Embedded Machine Learning information

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

What are the key skills and qualifications needed to thrive as a senior embedded machine learning engineer?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

What cities in Oregon are hiring for Senior Embedded Machine Learning jobs?

Cities in Oregon with the most Senior Embedded Machine Learning job openings:

Senior Embedded Machine Learning jobs near you

Senior Machine Learning Engineer, Digital Twin Platform

OR • On-site, Remote

Instacart
Technology, Communication and Media • 10K+ employees
Learn more about Instacartexternal

$122K - $161K/yr

Full-time

Posted 21 days ago

Key responsibilities

  • Design, develop, and deploy machine learning models that understand in-store inventory levels and shelf stocking dynamics in real time.

  • Own the full machine learning lifecycle from problem framing and data exploration to model training, evaluation, and deployment.

  • Collaborate with cross-functional teams to integrate models into live products and contribute to building the platform's core infrastructure.

Instacart rating

6.4

Company rating: 6.4 out of 10

Based on 34 frontline employees who took The Breakroom Quiz

Job description

Overview

The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times - bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.

We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.

You can read more about some of the work this team is doing here:

Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes

Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence

About the Job
  • Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.
  • Own the full ML lifecycle - from problem framing and data exploration through model training, evaluation, and production deployment - with a focus on quality, reliability, and measurable business impact.
  • Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.
  • Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.
  • Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed - expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.
About You

Minimum Qualifications

  • 5+ years of experience developing and deploying machine learning models in production environments.
  • Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.
  • Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.
  • Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.

Preferred Qualifications

  • Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems.
  • Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments.
  • Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight.
  • Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows and is consumed in those contexts.
  • Experience collaborating closely with computer vision teams or incorporating vision-based signals into broader ML systems.

#LI-Remote

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012

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