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Remote Machine Learning Compiler Engineer Jobs in Largo, MD

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Halvik

Machine Learning Engineer - Remote

Mclean, VA · On-site +1

$140K - $150K/yr

Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch ...

Halvik

Machine Learning Engineer - Remote

Mclean, VA · Remote

$115K - $139K/yr

Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch ...

New

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

Capital One

Senior Machine Learning Engineer

Mclean, VA · On-site +1

$105K - $145K/yr

Senior Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

New

Capital One

Staff Machine Learning Engineer

Mclean, VA · On-site +1

Staff Machine Learning Engineer Overview: As a Capital One Machine Learning Engineer, you'll be providing technical leadership to engineering teams dedicated to productionizing machine learning ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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All JobsMachine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer JobsRemote Machine Learning Compiler Engineer Jobs in Largo, MD

Remote Machine Learning Compiler Engineer information

See Largo, MD salary details

$76.4K

$170.6K

$208.9K

How much do remote machine learning compiler engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for remote machine learning compiler engineer in Largo, MD is $170,624.00, according to ZipRecruiter salary data. Most workers in this role earn between $145,700.00 and $208,900.00 per year, depending on experience, location, and employer.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Largo, MD?

For Remote Machine Learning Compiler Engineer jobs in Largo, MD, the most frequently searched job titles are:

What cities near Largo, MD are hiring for Remote Machine Learning Compiler Engineer jobs?

Cities near Largo, MD with the most Remote Machine Learning Compiler Engineer job openings:

Remote Machine Learning Compiler Engineer jobs near you
Infographic showing various Remote Machine Learning Compiler Engineer job openings in Largo, MD as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $170,624 per year, or $82 per hour.

Machine Learning Engineer

Washington, DC • On-site, Remote

Spear AI
Guided Missile and Space Vehicle Manufacturing • 11 - 50 employees
Learn more about Spear AIexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 28 days ago

Key responsibilities

  • 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

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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