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Embedded Machine Learning Jobs in Pittsburgh, PA

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site +1

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ... Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference) * Familiarity with ...

Gather AI

Principal Machine Learning Scientist

Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets What You'll Need * 10+ years of experience in machine learning or ...

Motional

Senior Embedded Software Engineer

Pittsburgh, PA · On-site +1

$120K - $157K/yr

... machine learning, sensors, and hardware compute platforms to evolve Motional's next-generation on ... If you are a software engineer and love the idea of working on embedded AI hardware and software ...

Motional

Senior Embedded Software Engineer

Pittsburgh, PA · On-site

$149K - $198K/yr

Design test harnesses for embedded software components and full systems * Provide technical ... Experience deploying Machine Learning models. * Experience working with GPUs. * Experience working ...

Motional

Senior Embedded Software Engineer

Pittsburgh, PA · On-site +1

$149K - $198K/yr

Design test harnesses for embedded software components and full systems * Provide technical ... Experience deploying Machine Learning models. * Experience working with GPUs. * Experience working ...

HELLBENDER Inc.

Perception Engineer

Pittsburgh, PA · Hybrid

Experience deploying machine learning models on embedded platforms, such as NVIDIA Jetson or Hailo TPUs, is highly preferred Job Type: Full-time Benefits: * 401(k) * 5% Safe Harbor Contribution to ...

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All JobsEmbedded Machine Learning JobsEmbedded Machine Learning Jobs in Pittsburgh, PA

Embedded Machine Learning information

See Pittsburgh, PA salary details

$68K

$148.9K

$168.9K

How much do embedded machine learning jobs pay per year?

As of Jun 25, 2026, the average yearly pay for embedded machine learning in Pittsburgh, PA is $148,907.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,700.00 and $168,000.00 per year, depending on experience, location, and employer.

Will AI replace embedded programmers?

Embedded machine learning involves developing algorithms for resource-constrained devices, and while AI tools can assist with coding and optimization, embedded programmers are essential for designing, implementing, and maintaining these systems. AI is more likely to augment their work rather than fully replace them, especially given the need for specialized knowledge of hardware and real-time constraints.

Is embedded AI a good career?

Embedded machine learning involves developing AI models for hardware with limited resources, such as IoT devices and embedded systems. It is a growing field with demand for skills in hardware programming, C/C++, and AI frameworks, offering opportunities in industries like automotive, healthcare, and consumer electronics.

Is embedded systems still a good career in 2026?

Embedded Machine Learning remains a strong career in 2026 as industries increasingly adopt AI-powered devices and IoT solutions. Professionals with skills in hardware programming, real-time systems, and machine learning frameworks like TensorFlow Lite are in demand for developing intelligent embedded applications. Continuous learning and familiarity with microcontrollers, sensors, and embedded software development are essential for long-term growth in this field.

What engineers make $500,000?

Senior engineers in specialized fields such as embedded machine learning, AI, or data science can reach salaries of $500,000 or more, especially with extensive experience, advanced skills in programming and hardware, and leadership roles. High compensation often involves working in high-demand industries, with additional bonuses or stock options contributing to total earnings.

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

Professionals in embedded machine learning roles often face the challenge of optimizing machine learning models to run efficiently on resource-constrained hardware, such as microcontrollers or edge devices with limited memory and processing power. Balancing model accuracy, inference speed, and energy consumption can require creative problem-solving and deep knowledge of both hardware and software. Additionally, collaboration with hardware engineers, data scientists, and software developers is key, as projects typically require cross-functional teamwork to meet performance and deployment goals. Staying current with rapidly evolving tools and best practices is also important in this dynamic field.

What is an Embedded Machine Learning job?

An Embedded Machine Learning job involves developing and optimizing machine learning models to run efficiently on resource-constrained devices like microcontrollers, edge devices, and IoT hardware. Professionals in this role work on model compression, low-power inference, and real-time processing, ensuring AI capabilities can function without relying on cloud computing. Responsibilities often include data preprocessing, feature extraction, model training, and deployment on embedded systems using frameworks like TensorFlow Lite or Edge Impulse.

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

To thrive in Embedded Machine Learning, you should have expertise in machine learning algorithms, embedded systems programming (e.g., C/C++, Python), and a solid understanding of hardware-software integration, typically backed by a degree in computer engineering, electrical engineering, or a related field. Familiarity with edge AI tools (such as TensorFlow Lite, ONNX, or Edge Impulse), microcontrollers, and real-time operating systems is highly valued, alongside relevant certifications such as Embedded Systems or AI certificates. Strong problem-solving skills, effective communication, and the ability to work cross-functionally are crucial soft skills in this field. These qualifications and qualities are vital for creating efficient, reliable AI solutions that operate seamlessly within resource-constrained environments and interdisciplinary project teams.

What are the most commonly searched types of Embedded Machine Learning jobs in Pittsburgh, PA? The most popular types of Embedded Machine Learning jobs in Pittsburgh, PA are:
What are popular job titles related to Embedded Machine Learning jobs in Pittsburgh, PA? For Embedded Machine Learning jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning jobs in Pittsburgh, PA look for? The top searched job categories for Embedded Machine Learning jobs in Pittsburgh, PA are:
Embedded Machine Learning jobs near you
Infographic showing various Embedded Machine Learning job openings in Pittsburgh, PA as of June 2026, with employment types broken down into 72% Full Time, 24% Part Time, and 4% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $148,907 per year, or $71.6 per hour.
Director of Machine Learning

Director of Machine Learning

Gather AI

Pittsburgh, PA

Full-time

Posted 23 days ago

Job description

About Us

Are you ready to build the future of supply chain? At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.

If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About the Team

You'll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you'll collaborate with Product and Business leadership to translate ML capabilities into product value. This is a high-visibility role with a direct line to executive leadership and significant influence over product direction.

About the Role

We are looking for a Director of Machine Learning to define our ML strategy, lead our computer vision organization, and drive the next phase of ML maturity at Gather AI. You will assess existing ML and CV capabilities, identify gaps and opportunities, and establish a clear technical vision for how machine learning will power our warehouse intelligence platform over the next 12–18 months.

The ideal candidate brings deep computer vision expertise, a track record of shipping production ML systems, and the leadership experience to build and scale a world-class ML team.

What You'll Do

  • Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives
  • Lead and grow the Machine Learning and FPT teams, establishing a culture of rigor, experimentation, and production-quality delivery
  • Drive improvements to core computer vision models (object detection, segmentation, OCR) used across our drone and MHE Vision products
  • Build out MLOps infrastructure — model training pipelines, deployment, monitoring, and CI/CD for ML workloads
  • Collaborate with the Director of Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the broader platform
  • Partner with Product and Operations to translate customer needs into ML-driven product capabilities

What You'll Need

  • 10+ years building and scaling production ML or computer vision systems
  • 5+ years managing and growing ML engineering teams
  • Deep expertise in computer vision: object detection, image segmentation, OCR, and CNN architectures
  • Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to production at scale
  • MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree)

Nice to Have

  • Experience with drone, robotics, or autonomous systems perception
  • Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference)
  • Familiarity with warehouse, logistics, or supply chain domain
  • Experience with AWS or GCP ML services (SageMaker, Vertex AI)