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Senior Embedded Machine Learning Jobs in Oregon (NOW HIRING)

Upstart

Senior Manager, Privacy Engineering

OR · On-site +1

$100K - $128K/yr

The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning to embed privacy-by-design into how Upstart builds, uses, retains, and governs data. As the Senior ...

Pwc

CTIO - AI Engineer- Senior Manager

Portland, OR · On-site

$91K - $321K/yr

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

Netflix

Machine Learning Scientist 5 - Sales, Ads DSE

OR · On-site +1

$466K - $750K/yr

... machine learning to help sellers work smarter, close more deals, and scale Ads revenue without ... Serve as a senior technical voice in cross-functional discussions, communicating clearly with both ...

Upstart

Senior Software Engineer, Marketplace Optimization

OR · On-site +1

$122K - $161K/yr

As a Senior Software Engineer, you'll partner closely with Product, Machine Learning, Pricing, Capital Markets, Lending Partnerships, and Analytics to build highly reliable distributed systems that ...

Upstart

Senior Privacy Engineer

OR · On-site +1

$104K - $143K/yr

The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning to make privacy-by-design practical and scalable. As a Privacy Engineer II at Upstart, you will ...

Agility Robotics

Staff AI Engineer, Perception

Salem, OR · On-site +1

$207K - $323K/yr

Design, develop, and deploy machine learning algorithms for multi-object detection, scene ... Optimize deep neural networks and associated data processing to run efficiently on embedded systems

SentinelOne

Senior Backend Software Engineer, ObservoAI

OR · On-site +1

$122K - $161K/yr

As a Senior Software Engineer, you will be tasked with leading the architectural design and ... using advanced machine learning and LLMs. * Design cloud-native microservices and APIs that ...

Fuze Health

Senior Manager, Data Engineering

OR · On-site +1

As the Senior Manager, Data Engineering, you will lead the strategy, architecture, and execution of ... Collaborate closely with Data Science and Machine Learning teams to ensure the platform scales ...

Versapay

Senior Data Engineer

OR · On-site +1

$105K - $143K/yr

Operationalize Machine Learning: Design and maintain MLOps pipelines to support the seamless ... Direct experience architecting data products for commercialization, external endpoints, or embedded ...

Five9

Senior Product Manager, AI Innovations - Agent Assist

OR · On-site +1

$126K - $166K/yr

We are seeking an experienced and strategic Senior Product Manager to lead the development of our ... Operating at the intersection of advanced machine learning and human-centric design, you will ...

BetterHelp

Staff ML/AI Platform Engineer

OR · On-site +1

This role will work closely with the Sr. Director of ML/Data Engineering and will have an important role in setting up the direction of the machine learning efforts, hiring successful talent, and ...

Upstart

Senior Software Engineer, Home Lending

OR · On-site +1

$122K - $161K/yr

As a Senior Software Engineer on the team, you will own the reliability, quality, and forward ... and Machine Learning, Servicing, and Operations. How you'll make an impact Build and improve ...

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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 are the most commonly searched types of Embedded Machine Learning jobs in Oregon?

The most popular types of Embedded Machine Learning jobs in Oregon are:

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 Manager, Privacy Engineering

Upstart

OR • On-site, Remote

$100K - $128K/yr

Full-time

Re-posted 21 days ago

Upstart rating

7.6

Company rating: 7.6 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

The Team

Upstart's Privacy Engineering team builds the systems, controls, and practices that help protect borrower, applicant, partner, and Upstarter data across our products and platforms. The team works across Engineering, Security, Legal, Compliance, Product, Data, and Machine Learning to embed privacy-by-design into how Upstart builds, uses, retains, and governs data.
As the Senior Manager, Privacy Engineering at Upstart, you will lead the team responsible for building scalable privacy infrastructure and technical privacy controls across Upstart's AI lending marketplace. You will set the team's roadmap, grow and support privacy engineers, and help translate privacy and regulatory requirements into durable engineering systems.


How you'll make an impact

  • Lead the Privacy Engineering team's strategy, roadmap, and execution across privacy infrastructure, data governance, and privacy-by-design initiatives
  • Hire, coach, and develop a team of privacy engineers while establishing clear operating rhythms, priorities, and technical standards
  • Guide the design and delivery of scalable privacy controls, including data discovery, classification, access controls, audit logging, retention, deletion, lineage, encryption, and key management
  • Partner with Legal, Compliance, Security, Product, Data, Machine Learning, and Infrastructure teams to translate privacy requirements into practical technical solutions
  • Oversee privacy reviews, technical risk assessments, and threat modeling for new products, data flows, models, and platform capabilities
  • Define metrics and communicate progress, tradeoffs, dependencies, and risks to technical and cross-functional stakeholder

Minimum Qualifications

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience, and 8+ years of experience in engineering, including at least 3 years of direct people management experience
  • Experience leading engineering teams responsible for production software, platform, privacy, security, or data systems
  • Experience designing, building, or operating privacy, security, data governance, or data platform capabilities in production environments
  • Experience translating privacy, security, compliance, or regulatory requirements into technical controls
  • Experience working with cross-functional partners such as Legal, Compliance, Security, Product, Data, or Machine Learning teams

Preferred Qualifications

  • Knowledge of privacy-by-design principles, data minimization, purpose limitation, consent, retention, deletion, and data subject rights
  • Knowledge of privacy and data protection regulations or frameworks such as GDPR, CCPA/CPRA, GLBA, FCRA, or similar requirements
  • Experience with privacy reviews, threat modeling, risk assessments, data inventories, lineage systems, or automated policy enforcement
  • Experience building privacy or governance controls for machine learning, AI, financial services, lending, or other regulated data environments
  • Ability to communicate technical privacy tradeoffs clearly across engineering, legal, product, security, and business audiences

Travel requirements As a digital first company, the majority of your work can be accomplished remotely. The majority of our employees can live and work anywhere in the U.S but are encouraged to to still spend high quality time in-person collaborating via regular onsites. The in-person sessions' cadence varies depending on the team and role; most teams meet once or twice per quarter for 2-4 consecutive days at a time.

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