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Embedded Machine Learning Internship Jobs in Maryland

Position Embedded Systems Software Engineer * Location: Churchville, MD * Security Clearance ... Artificial Intelligence/Machine Learning (AI/ML), Neural Networks, or computer vision About Us ...

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Embedded Machine Learning Internship information

What is an Embedded Machine Learning Internship?

An Embedded Machine Learning Internship is a temporary position designed for students or recent graduates to gain hands-on experience in developing and deploying machine learning algorithms on embedded systems. These internships typically involve working with hardware such as microcontrollers, sensors, or edge devices, and using specialized tools to optimize machine learning models for low-power and resource-constrained environments. Interns collaborate with engineers and data scientists to create efficient, real-world AI solutions that run directly on devices rather than relying on cloud computing. This role helps bridge the gap between theoretical machine learning concepts and practical implementation on embedded platforms.

What are some typical projects or tasks I might work on during an Embedded Machine Learning Internship?

During an Embedded Machine Learning Internship, you can expect to work on projects such as optimizing machine learning models to run efficiently on hardware with limited resources, integrating AI algorithms into embedded systems (like microcontrollers or IoT devices), and performing real-time data processing. You'll likely collaborate closely with software engineers and hardware designers to test models on physical devices, debug performance issues, and contribute to documentation. These experiences provide practical exposure to the challenges of deploying AI in real-world, resource-constrained environments and help build skills valuable for a future career in embedded AI.

What are the key skills and qualifications needed to thrive as an Embedded Machine Learning Intern, and why are they important?

To thrive as an Embedded Machine Learning Intern, you need a background in computer science, electrical engineering, or a related field with strong programming skills in C/C++ and Python, as well as foundational knowledge of machine learning algorithms. Experience with embedded systems development tools (such as ARM Cortex, Raspberry Pi, or Arduino), version control systems, and familiarity with ML frameworks like TensorFlow Lite or Edge Impulse is often required. Analytical thinking, problem-solving ability, and effective teamwork are vital soft skills for success in this role. These skills and qualities are crucial for efficiently developing, optimizing, and deploying machine learning solutions on resource-constrained embedded platforms.
What are the most commonly searched types of Embedded Machine Learning jobs in Maryland? The most popular types of Embedded Machine Learning jobs in Maryland are:
What are popular job titles related to Embedded Machine Learning Internship jobs in Maryland? For Embedded Machine Learning Internship jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Embedded Machine Learning Internship jobs in Maryland look for? The top searched job categories for Embedded Machine Learning Internship jobs in Maryland are:
What cities in Maryland are hiring for Embedded Machine Learning Internship jobs? Cities in Maryland with the most Embedded Machine Learning Internship job openings:
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Xometry

Silver Spring, MD

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 3 days ago


Job description

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.
We are looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact. You will lead the design and delivery of complex ML systems, architect integrations across our tech stack, and set the engineering standard for how we build and deploy machine learning solutions at scale. You will work closely with data scientists, engineers, and product managers to bring high-impact ML capabilities into production. Everything you build will matter. A defining piece of this role is owning the AI/ML architecture behind one of Xometry's highest-leverage strategic initiatives: the DFM AI + IQE integration. You will be the data engineering lead for the digital thread that connects Xometry's platform to our partner's ecosystem - Solid Edge, NX, Designcenter, and Teamcenter - building the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between the two systems in real time. The system you design is what takes the innovative digital thread operating at "science fiction speed" from ideation to reality.
Responsibilities

  • Lead with technical depth - Own the end-to-end lifecycle from requirements gathering through release, ensuring high-quality, on-time delivery across complex, cross-functional initiatives.
  • Own the Partner integration AI/ML plane - Architect and build the high-performance AI/ML layer of Xometry's embedded DFM AI + IQE integration with Teamcenter and Designcenter. You will be responsible for designing the real-time ML serving architecture and the low-latency signal path that delivers DFM and pricing feedback directly into the designer's environment. This includes defining the data contracts for model inputs/outputs and implementing the MLOps, governance, and observability required for a mission-critical, public-marketplace partner integration.
  • Build for scale - Develop cloud-based production systems powering real-time endpoints and MLOps, integrated with Xometry's broader systems and infrastructure.
  • Solve ambiguous problems - Navigate complex, cross-domain technical challenges, evaluate variable factors, and deliver solutions that meet both business and technical objectives.
  • Set the Standard - Proactively surface opportunity areas, take ownership of new processes and solutions, and develop multi-quarter roadmaps to accomplish key technical objectives.
  • Champion quality and security - Apply best practices in automated testing, parallel and distributed computing, and secure software development across ML systems.
  • Collaborate broadly - Partner with engineers, product managers, data scientists, and business stakeholders to translate requirements into robust technical solutions.
  • Mentor and elevate - Guide other engineers through design reviews, code reviews, and technical mentorship, raising the overall capability of the team.
  • Stay current - Keep pace with advances in ML/AI and bring relevant new approaches, tools, and frameworks into practice.
Qualifications
  • Bachelor's degree in a STEM field (or equivalent experience) plus 6-8 years of experience in machine learning engineering, with a track record of owning and delivering complex ML systems in production.
  • Deep expertise in ML and AI technologies, including Gradient Boosting methods, Deep Learning, and/or Generative AI frameworks, with a focus on backend scalability and
    reusability.
  • Hands-on experience deploying real-time ML products at scale in cloud environments (AWS strongly preferred), including auto-scaling, monitoring, and alerting.
  • Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow, PyTorch, or similar.
  • Solid grounding in software engineering fundamentals, data structures, and algorithms.
  • Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines.
  • Proficiency with CI/CD pipelines (e.g., Github actions),test driven development, and infrastructure as code (e.g., Terraform).
  • Experience profiling and optimizing existing ML model deployments for latency and throughput.
  • Ability to operate independently on new and ambiguous assignments, determine methods and procedures, and communicate effectively across engineering, product, and
    business audiences.
  • Experience with state-of-the-art modeling techniques including transformers, self-supervised pre-training, large language models (LLMs), or generative AI.
  • Knowledge of containers, container orchestration (Kubernetes), and cloud-native distributed systems.
  • Background in manufacturing, supply chain, or marketplace environments is a plus - but curiosity and drive matter more.

The estimated base salary range for new hires into this role is $200,000-$220,000.00 annually + commission depending on factors such as job-related skills, relevant experience, and location. We also offer a competitive benefits package, including 401(k) match, medical, dental and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; EAP, other wellbeing resources; and much more.
#LI-Hybrid
Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.
For US based roles: Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.

Xometry logo

About Xometry

Sourced by ZipRecruiter

Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry's digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity.

Industry

Software development

Company size

501 - 1,000 Employees

Headquarters location

Gaithersburg, MD, US

Year founded

2013