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Senior Machine Learning Engineer Jobs in Broad Run, VA

J5 Consulting

Machine Learning Engineer

Herndon, VA · On-site

$117K - $141K/yr

They are seeking a Machine Learning Engineer to provide analytical support for compliance with Federal data standards, data cleansing, transformation, and data migration planning. Responsibilities ...

Unissant

Machine Learning Engineer

Ashburn, VA · On-site

$112K - $177K/yr

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough ...

Tetra Tech

Machine Learning Engineer - Remote

Vienna, VA · On-site

$120 - $180/hr

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

Vienna, 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

Vienna, VA · On-site

$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, TensorFlow)

SAIC

AI/Machine Learning Engineer Principal

Chantilly, VA · On-site

$120K - $160K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance Required: TS.SCI_wPoly Clearance Level Must Be Able to Obtain: None Potential for Remote ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Broad Run, VA

Senior Machine Learning Engineer information

See Broad Run, VA salary details

$57.5K

$122.4K

$177.4K

How much do senior machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for senior machine learning engineer in Broad Run, VA is $122,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,100.00 and $138,800.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Broad Run, VA are hiring for Senior Machine Learning Engineer jobs?

Cities near Broad Run, VA with the most Senior Machine Learning Engineer job openings:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Broad Run, VA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $122,381 per year, or $58.8 per hour.

Senior Machine Learning Engineer, Radar & Remote Sensing

Jobtailor

Chantilly, VA • On-site

$180 - $240/hr

Other

Posted 10 days ago

Job description

  • Own the radar and ML technical stack across radar/SAR simulation, machine learning, scientific software, and compute infrastructure
  • Act as a technical liaison between radar engineering, machine learning, software engineering, and operations teams
  • Develop and maintain radar and SAR simulation pipelines, including synthetic data generation, scene/return modeling, and validation workflows
  • Design, build, and refine end-to-end ML models and pipelines for radar-related tasks
  • Perform preprocessing, training, evaluation, and deployment-ready packaging
  • Utilize and analyze radar, 3D model, EO/IR, and sensing‑adjacent defense datasets
  • Create radar products and technical deliverables, including APIs, data schemas, containers, documentation, and integration guidance
  • Design, configure, and optimize local compute environments, GPU/eGPU setups, remote compute, storage, networking, containerization, and benchmarking
  • Support ML inference/training on constrained or embedded compute, including RFSoCs and FPGAs
  • Collaborate with RF/hardware partners on RF code processing, radar outputs, and deployable radar hardware productization
  • Help deploy and maintain web applications and internal tools on classified or restricted networks
  • Contribute to technical writing, SBIR proposals, and system documentation
Requirements
  • Active TS/SCI clearance
  • US Citizenship is required
  • Deep experience in Synthetic Aperture Radar, non-imaging radar, remote sensing, or signal processing
  • Solid understanding of radar/SAR fundamentals, including I/Q and complex‑valued data, simulation techniques, image formation algorithms and radar‑to‑image pipelines, and coherent vs. incoherent processing
  • Proven experience with radar or remote sensing simulations
  • Strong proficiency with scientific Python libraries, including NumPy, PyTorch, SciPy, Matplotlib, Jupyter, and related scientific stacks
  • Ability to build end-to-end ML pipelines encompassing data preprocessing, training, evaluation, versioning, packaging, and hand‑off to other engineers
  • Hands‑on experience with GPU compute, including PyTorch, CUDA, NVIDIA tooling, remote GPU servers, and local GPU compute
  • Ability to explain radar/ML concepts to non‑radar engineers and produce clear technical deliverables
  • Adherence to software engineering principles and best practices, including clean code, testing, and version control
  • Exceptional communication skills and ability to produce high‑quality technical documentation and deliverables
  • Prolonged periods sitting at a desk and working on a computer
  • Must be able to lift up to 10–15 pounds at a time
Core Competencies

Demonstrates expertise in Synthetic Aperture Radar and machine learning, with a strong ability to develop and maintain radar simulation pipelines and end-to-end ML models. Proficient in scientific Python libraries and GPU compute, with a focus on producing clear technical documentation and deliverables.

Highest‑signal resume keywords
  • Synthetic Aperture Radar Expertise
  • End‑to‑End ML Pipeline Development
  • Scientific Python Proficiency
  • GPU Compute Experience ATS Optimization Keywords Hard Skills
    • Radar Simulation
    • Machine Learning Models
    • Data Preprocessing
    • Image Formation Algorithms
    • Version Control
    • Testing Best Practices
    • Synthetic Data Generation
    • Scene/Return Modeling
    • Coherent Processing
    • Non‑Imaging Radar
    Soft Skills
    • Exceptional Communication Skills
    • Technical Writing
    Certifications & Qualifications
    • Active TS/SCI Clearance
    • US Citizenship
    Industry Keywords
    • Remote Sensing
    • Signal Processing
    • Radar Fundamentals
    • RF Code Processing
    • Embedded Compute
    • Technical Deliverables
    • SBIR Proposals
    • Compute Infrastructure
    • Data Schemas
    • Integration Guidance
    Tools & Technologies
    • NumPy
    • PyTorch
    • SciPy
    • Matplotlib
    • Jupyter
    • CUDA
    • NVIDIA Tooling
    • Remote GPU Servers
    • Containerization
    • APIs
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