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Edge Ai Machine Learning Jobs in Washington, DC (NOW HIRING)

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

Spear AI is a growing defense contracting company dedicated to delivering cutting-edge solutions ... Integrate machine learning models into real-time and batch processing systems * Optimize model ...

i3

AI/Machine Learning Engineer SME

Washington, DC · Hybrid

$200K - $350K/yr

Overview Integration Innovation, Inc. (i3) is seeking a motivated SME level AI/Machine Learning Engineer to support the Defense Intelligence Agency (DIA) Enterprise Data Management & Analytics (EDMA ...

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How much do edge ai machine learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for edge ai machine learning in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

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Edge Ai Machine Learning jobs near you

Machine Learning Engineer

Spear AI

Washington, DC • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago

Job description

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

Spear AI is a growing defense contracting company dedicated to delivering cutting-edge solutions that support our nation's security. As we expand, we're building a culture where innovation meets mission-critical work. We operate with a flat organizational structure that empowers every team member to make an impact, collaborate directly with leadership, and contribute to projects that matter. Whether you're joining our Hardware, Software, or Services division, you'll work alongside talented professionals who are committed to excellence and advancing the capabilities that keep our nation safe and secure.
Spear AI builds sonobuoy sensors that are deployed into the water and collect edge data. We also work with the U.S. Navy to collect and process their SONAR data. You'll have an opportunity to work on real-world projects that directly impact warfighter capabilities and mission success.
What You'll Do
  • We're a small team wearing many hats, and you'd have a wide variety of responsibilities that include:
  • Design, train, and optimize machine learning models using PyTorch
  • Deploy models to production environments in the cloud and at the edge
  • Build and maintain ML pipelines for training, evaluation, and inference
  • Integrate machine learning models into real-time and batch processing systems
  • Optimize model performance for accuracy, latency, and resource constraints
  • Implement model monitoring, versioning, and deployment strategies
  • Work with signal processing data and time-series analysis
  • Improve local development and CI/CD for ML workflows using modern tooling and GitHub Actions
Who You Are
  • We're looking for someone with strong Machine Learning Engineering skills who shares our most important values:
  • You're fanatical about polish. Every detail matters. You love to make sure your code is linted, formatted, fully typed, and has comprehensive test coverage.
  • You care about correctness. You take pride in the fact that your models perform reliably and downstream consumers trust your predictions.
  • You obsess over performance. You daydream about model latency, throughput, and efficient inference pipelines.
  • You dive deep. It's important for you to really know how things work. You're always building prototypes and setting up experiments to reinforce your understanding.
  • You live on the bleeding edge. You've got a long list of upcoming ML techniques and frameworks you're excited about and can't wait to experiment with new approaches.
  • You're a great teacher. You know how to break down complex ML concepts for a specific audience and make it click with them in a way that gets them excited.
Why Work With Us
  • We ship - We don't work on 18-month projects that are irrelevant before they're even finished.
  • Our work has impact - We build products that are deployed to U.S. submarines and integrate with the sonobuoys we manufacture.
  • We're growing responsibly - We have the resources to hire a lot more people, but we don't want to build a massive team of people who don't share our values.
  • We're remote - Work from wherever you want. We collaborate in real time on Slack or asynchronously via GitHub.
  • We're profitable - We aren't burning through cash trying to make the business work. But we also have investors who believe in us and are committed to our success.
  • We care about doing great work - You don't need permission to sweat the details here.
  • We don't take ourselves too seriously - We're building products that make the world safer. But we don't let that get to our heads.
Important Skills
  • Several years of experience with Python and machine learning frameworks
  • Expertise in PyTorch for building and training neural networks
  • Experience training and serving models in cloud environments (AWS, Azure, GCP)
  • Proficiency with MLOps practices including experiment tracking, model versioning, and deployment
  • Experience with model optimization for production performance and scale
  • Knowledge of Docker and Kubernetes for containerized deployments
  • Familiarity with REST APIs and model serving frameworks
  • Understanding of CI/CD pipelines for ML systems
  • Strong fundamentals in machine learning including model architecture design, training strategies, and evaluation
Nice To Have
  • Experience with reinforcement learning algorithms and applications
  • Digital signal processing experience
  • Background in time-series analysis or sensor data processing
  • Experience with edge deployment and model optimization for resource-constrained environments
  • Familiarity with distributed training across multiple GPUs/nodes
  • Experience with model compression techniques (quantization, pruning, distillation)
  • Contributions to open-source ML projects or research publications
  • Experience in defense, aerospace, or other regulated industries
What We Offer
  • Unlimited PTO - Take the time you need to recharge and maintain work-life balance.
  • Dedicated Sick Time - Your health and well-being come first.
  • Comprehensive Health & Benefits - Medical, dental, and vision coverage to keep you and your family protected.
  • 11 Paid Holidays - Enjoy time off throughout the year to celebrate and spend with loved ones.
  • Professional Development - Educational opportunities and resources to help you grow your skills and advance your career.
  • Collaborative Environment - Work directly with leadership in our flat organizational structure, where your ideas and contributions matter.
  • Mission-Driven Work - Contribute to projects that directly support national security and make a real-world impact.
  • Growth Opportunities - Join us during an exciting expansion phase where you can help shape our future.
Additional Benefit Opportunities When You Choose Spear AI:
  • 401(k) with company match
  • Onsite / Remote / Flexible work arrangements or hybrid options (position dependent)
  • Relocation assistance (position dependent)
  • Referral bonuses
  • Performance bonuses
  • Life insurance and disability coverage
  • Technology home office setup stipend
  • Professional certification reimbursement (position dependent)
We offer competitive compensation tailored to your experience, location, and the impact you'll make. We're committed to equitable pay and will share a range aligned to your level and geography during the hiring process. In accordance with state law, candidates in jurisdictions such as CA, CO, WA, NY, and others, where applicable, will be provided a good-faith salary range upon request and through the hiring process. This is a full-time, exempt position under the Fair Labor Standards Act (FLSA) and is not eligible for overtime pay.

Compensation for this position is provided on a salaried basis and is not subject to reduction based on hours worked. At Spear AI, you'll find more than just a job; you'll join a mission-driven team where your work directly contributes to national security. Our flat organizational structure means your voice matters, your ideas reach leadership, and your impact is visible. As we grow, we're committed to building robust processes and infrastructure that support both our mission and our people. We value collaboration, continuous improvement, and the expertise each team member brings to the table. If you're looking for a place to grow professionally while working on projects that truly matter, we'd love to hear from you.

You must be willing to receive a Secret or Top Secret/SCI security clearance. This will be at no expense to you. For resources on what goes into a security background investigation and what disqualifies people reference the CIA requirements.
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About Spear AI

Sourced by ZipRecruiter

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Washington, DC, US

Year founded

2020

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