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Remote Machine Learning Jobs in Glen Allen, VA (NOW HIRING)

Genworth Financial

Senior Software Engineer

Richmond, VA · On-site +1

$121K - $159K/yr

... by learning from the world and each other. SENIOR SOFTWARE ENGINEER This role is not eligible for Sponsorship. POSITION LOCATION Richmond, Virginia Open to Remote This position is available to ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Glen Allen, VA

Remote Machine Learning information

See Glen Allen, VA salary details

$24.1K

$40.2K

$83.1K

How much do remote machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote machine learning in Glen Allen, VA is $40,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,700.00 and $43,400.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

More about Remote Machine Learning jobs

What are popular job titles related to Remote Machine Learning jobs in Glen Allen, VA?

For Remote Machine Learning jobs in Glen Allen, VA, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning jobs in Glen Allen, VA look for?

The top searched job categories for Remote Machine Learning jobs in Glen Allen, VA are:

What cities near Glen Allen, VA are hiring for Remote Machine Learning jobs?

Cities near Glen Allen, VA with the most Remote Machine Learning job openings:

Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in Glen Allen, VA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $40,220 per year, or $19.3 per hour.

SENIOR AWS DATA-INTEGRATION AND DATA-QUALITY ENGINEER - Remote

Axyde Analytics

Midlothian, VA • Remote

$108K - $130K/yr

Full-time

Posted 15 days ago

Job description

Axyde Analytics seeks a senior AWS data engineer to design and implement managed-service data-ingestion, transformation, quality, cataloging, and monitoring capabilities for a federal enterprise analytics platform.

Responsibilities

  • Establish and maintain secure connections to heterogeneous Government and public data sources.

  • Ingest structured, semi-structured, and unstructured information.

  • Configure Amazon S3, AWS Glue Data Catalog, Glue Crawlers, Athena, Step Functions, EventBridge, and approved managed data-preparation services.

  • Design reusable patterns for JDBC, Oracle, Red Hat/Linux, APIs, files, PDFs, scheduled feeds, and unscheduled uploads.

  • Incorporate Government-furnished Spark-compatible transformation logic into the approved architecture.

  • Implement schema inference, standardization, validation, lineage, quality controls, and exception handling.

  • Detect connection failures, schema changes, stale data, duplicates, prohibited data, and other quality issues.

  • Support daily refresh requirements and scalable onboarding of new data sources.

  • Produce technical documentation, runbooks, data dictionaries, and source-to-interface mappings.

  • Support the live technical demonstration and subsequent production transition.

Required Experience

  • Five or more years of senior AWS data-engineering experience.

  • Strong hands-on experience with S3, Glue, Athena, Step Functions, EventBridge, and AWS-native monitoring.

  • Experience integrating relational databases, APIs, documents, and mixed-format enterprise data.

  • Demonstrated experience with data quality, metadata management, schema evolution, lineage, and operational monitoring.

  • Familiarity with Spark, PySpark, JavaSpark, or Spark transformation patterns.

  • Experience in federal, regulated, or sensitive-data environments strongly preferred.

Architecture Constraint

Implementation must remain within Axyde’s approved AWS managed-service baseline. Candidates must not assume that custom Python, Lambda, containers, EC2, third-party libraries, or external integration platforms may be used.

Engagement

U.S. citizenship required. Remote within the United States with occasional travel. Immediate proposal and demonstration support may be available; longer-term work is contingent upon award.