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Overnight Remote Machine Learning Jobs in Virginia

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Quora

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... LI-SS2 LI-REMOTE

Niyam IT, Inc.

AI Machine Learning Engineer

Ashburn, VA · On-site +1

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

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Overnight Remote Machine Learning information

What are Overnight Remote Machine Learning jobs?

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, and why are they important?

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 July 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.
Machine Learning Engineer - Remote

Machine Learning Engineer - Remote

Halvik

Vienna, VA • On-site, Remote

$140K - $150K/yr

Full-time

Posted 27 days ago

Job description

Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of something special!
Role and Responsibilities
Model Development
  • Collaborate with data scientists and SMEs to develop ML models using curated datasets.
  • Conduct experiments, prototypes, and proof-of-concepts to validate model performance.
  • Create scalable and reusable training pipelines using Databricks notebooks and MLflow.

Implementation and Optimisation
  • LLMs (Large Language Models), RAGs, and AI agent systems for various business applications. Deployment & MLOps
  • Operationalize models with robust CI/CD workflows.
  • Deploy models usingMLflow, SageMaker, or custom APIs.
  • Monitor production models for accuracy, drift, and latency; manage retraining schedules.

Data Integration & Architecture Alignment
  • Work closely with Data Engineering to align ML pipelines with the Bronze, Silver, Gold layers of a Medallion Architecture.
  • Engineer high-quality features and maintain training/inference pipelines.

Cloud and Platform Engineering
  • Leverage AWS services including S3, EC2, Lambda, SageMaker, and Step Functions.

Collaboration & Documentation
  • Document ML artifacts, processes, and performance outcomes.
  • Contribute to agile project ceremonies and maintain a feedback loop with stakeholders.
  • Share knowledge and mentor junior team members.

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).
  • Proficient with Databricks, MLflow, and PySpark.
  • Solid understanding of model lifecycle and MLOps practices.
  • Experience with AWS-based data infrastructure and related DevOps practices.
  • Demonstrated ability to productionize models and integrate with business system
  • Strong understanding of mathematics and statistics relevant to machine learning and AI.
  • Proven experience with machine learning models and algorithms (supervised, unsupervised, deep learning, etc.).
  • Solid background in software engineering principles and best practices.
  • Hands-on experience with model training frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Experience with MLOps tools and workflows, particularly on AWS (SageMaker, Lambda, S3, etc.).
  • Practical experience with LLMs, RAGs, and AI agent architectures.
  • Proficiency with the Databricks platform for data engineering and ML pipelines.
  • Advanced programming skills in Python.
  • Excellent communication and teamwork abilities.

Preferred Skills:
  • Experience building and deploying interactive UIs for AI models using Streamlit, Gradio, or similar frameworks for rapid prototyping and real-time model interactions
  • Business acumen and ability to align AI solutions with organizational goals.
  • Optimize compute and storage resources for performance and cost-efficiency.

Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Halvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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