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Overnight Remote Machine Learning Jobs in Virginia

SAIC

AI Machine Learning Developer Principal

Chantilly, VA · On-site +1

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

SAIC

AI Machine Learning Developer Principal

Arlington, VA · On-site +1

$160K - $200K/yr

Machine Learning Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum ... None Potential for Remote Work: ORA_HYBRID Description We are seeking to build a team of AI/ML ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

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Overnight Remote Machine Learning information

What is an overnight remote machine learning job?

Overnight Remote Machine Learning jobs are positions where professionals work on machine learning tasks outside of traditional office hours, typically during the night, and do so from a remote location. These roles may involve building models, analyzing data, or maintaining machine learning systems while collaborating with teams in different time zones or providing 24/7 support. Overnight shifts can be critical for companies with global operations or those that require continuous system monitoring. Working remotely allows for flexibility and access to a wider talent pool. These positions often require strong programming and analytical skills, as well as the ability to work independently with minimal supervision.

What are the key skills and qualifications needed to thrive as an overnight remote machine learning engineer?

To thrive as an Overnight Remote Machine Learning Engineer, you need strong programming skills (especially in Python), a solid background in statistics and algorithms, and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, experience with cloud platforms like AWS or GCP, and knowledge of version control systems are typically required. Excellent problem-solving abilities, self-motivation, and clear written communication are crucial soft skills for remote and overnight work schedules. These competencies ensure that you can efficiently develop, deploy, and monitor machine learning models independently while collaborating across time zones.

What are some common challenges faced by overnight remote machine learning professionals, and how can they be addressed?

Overnight remote machine learning professionals often encounter challenges like coordinating with daytime teams across different time zones, maintaining effective communication, and managing alertness during non-traditional hours. To address these, it's helpful to establish clear communication protocols, use collaboration tools for asynchronous updates, and set a structured sleep and work routine to ensure productivity. Additionally, leveraging automated monitoring and robust documentation helps in managing handoffs and reducing errors during shift changes.

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

AspectOvernight Remote Machine LearningData Scientist
CredentialsBachelor's or higher in CS, ML, or related fields; certifications like AWS, TensorFlowBachelor's or higher in CS, Statistics, or related fields; advanced degrees common
Work EnvironmentRemote, overnight shifts, focused on model deployment and data pipelinesOffice or remote, standard hours, focused on data analysis and model development
Industry UsageTech, finance, healthcare companies with 24/7 operationsResearch, tech, consulting firms, often with flexible hours

Overnight Remote Machine Learning roles typically focus on deploying models and maintaining data pipelines during overnight hours, often requiring specific certifications and remote work setups. Data Scientists usually work during regular hours, concentrating on data analysis, model development, and research. Both roles are vital in tech-driven industries but differ mainly in work hours, environment, and focus areas.

What are the most commonly searched types of Remote Machine Learning jobs in Virginia?

The most popular types of Remote Machine Learning jobs in Virginia are:

What are popular job titles related to Overnight Remote Machine Learning jobs in Virginia?

For Overnight Remote Machine Learning jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Overnight Remote Machine Learning jobs in Virginia look for?

The top searched job categories for Overnight Remote Machine Learning jobs in Virginia are:

Overnight Remote Machine Learning jobs near you
Infographic showing various Overnight Remote Machine Learning job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer, Radar & Remote Sensing

Chantilly, VA • On-site, Remote

NT Concepts
IT Services • 51 - 200 employees
Learn more about NT Conceptsexternal

$107K - $146K/yr

Full-time

Posted 20 days ago

Job description

Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. We're looking for the best and the brightest to join us in supporting this mission. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, join our growing team and discover What's Next for you. We tackle hard problems to meet our clients' needs.
We are looking for an applied engineer to own our radar and ML technical stack. This is a blended role at the intersection of radar/SAR simulation, machine learning, scientific software, and compute infrastructure.
The ideal candidate is not a pure data scientist or a pure signal processing engineer. They are a technical owner who can move across the stack: from radar simulations and data preprocessing to ML model development, local GPU/compute setup, and hand-offs of radar products to software and hardware teams.
Clearance: Active TS/SCI clearance. US Citizenship is required.
Location: Chantilly, VA (Monday-Thursday Onsite & Friday Remote)
Responsibilities:
  • Act as a technical liaison, fostering effective communication and collaboration between radar engineering, machine learning, software engineering, and operation teams.
  • Develop and maintain robust 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, including preprocessing, training, evaluation, and deployment-ready packaging.
  • Utilize and analyze defense-focused datasets, including radar, 3D models, Electro-Optical/Infrared (EO/IR), and sensing-adjacent data.
  • Create radar products and technical deliverables for internal software teams and hardware partners, including APIs, data schemas, containers, documentation, and integration guidance.
  • Design, configure, and optimize local compute environments, including GPU/eGPU setups, remote compute, storage, networking, containerization, and benchmarking.
  • Support ML inference/training on constrained or embedded compute, with awareness of systems such as RFSoCs, FPGAs, and related hardware constraints.
  • Collaborate with RF/hardware partners to support internal RF code processing, radar outputs, and productization of deployable radar hardware
  • Help deploy and maintain web applications and internal tools on classified or restricted networks.
  • Contribute to technical writing, SBIR proposals, and system documentation.

Required Qualifications:
  • 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
    • Coherent vs. incoherent processing
  • Proven track record of experience with radar or remote sensing simulations
  • Strong proficiency with scientific Python libraries:
    • NumPy, PyTorch, SciPy, Matplotlib, Jupyter, and related scientific stacks
  • Demonstrated ability to build end- to-end ML pipelines encompassing:
    • Data preprocessing
    • Training
    • Evaluation
    • Versioning
    • Packaging
    • Hand-off to other engineers
  • Hands-on experience with GPU compute, such as:
    • PyTorch
    • CUDA
    • NVIDIA tooling
    • Remote GPU Servers
    • Local GPU compute
  • Ability to explain radar/ML concepts to non-radar engineers and produce clear technical deliverables
  • Adherence to robust software engineering principles and best practices (e.g. clean code, testing, version control).
  • Exceptional communication skills, with the ability to clearly articulate complex radar and ML concepts to both technical and non-technical audiences, and to produce high-quality technical documentation and deliverables.

Preferred Skills/Experience:
  • Experience with Xpatch simulations specifically
  • Experience with CAD and or artistic 3D modeling skills
  • Experience with EO/IR or multi-sensor fusion
  • Experience with adversarial imaging AI
  • Understanding of RFSoCs, FPGAs, HLS, quantization, or edge deployment constraints
  • Experience designing or optimizing local compute servers / GPU clusters / eGPU configurations
  • Experience working with RF hardware partners or hardware-in-the-loop systems
  • Experience with LLMs, LoRA fine-tuning, or local model deployment for niche tasks
  • Experience with container computing and orchestration

Physical Requirements:
  • Prolonged periods sitting at a desk and working on a computer
  • Must be able to lift up to 10-15 pounds at time

#JT
The pay range listed for this position reflects the wage or salary range NT Concepts expects to pay for this role at the time of posting. The compensation offered to a successful candidate within this range will be based on legitimate, job-related factors, including (but not limited to) the candidate's work location, education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements.
Virginia Pay Range
$131,376-$243,984 USD
About NT Concepts
Founded in 1998 and headquartered in the Washington DC Metro area, NT Concepts is a private, mid-tier company with clients spanning the Intelligence and Defense communities. We deliver end-to-end data and technology solutions that advance the modernization, transformation, and automation of the national security mission-solutions with real impact developed in a strong engineering culture that encourages technical growth, leadership, and creative "big idea" problem-solving.
Employees are the core of NT Concepts. We understand that world-changing concepts happen in collaborative environments. We are a company where talented teams work together using innovation and expertise to solve our clients' most critical challenges. Here, you'll gain competitive benefits, opportunities to bolster your skills and develop new abilities, and a company culture dedicated to support and service. In addition to our benefits program, we encourage our employees to take part in #NTC_GivesBack, which paves the way for positive social change.
If joining a stable company with strong professional growth opportunities resonates with you, and you seek vital, mission-driven projects (for some pretty cool clients) that use your specific talents, we'd love to have you move forward with us.

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