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Remote Machine Learning Jobs in McLean, VA (NOW HIRING)

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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Remote Machine Learning information

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$25.8K

$43K

$89K

How much do remote machine learning jobs pay per year?

As of Jun 15, 2026, the average yearly pay for remote machine learning in McLean, VA is $43,046.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,900.00 and $46,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Engineer, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

Can I work remotely as a machine learning engineer?

Yes, many machine learning engineer roles are available for remote work, especially in companies that support flexible or distributed teams. Remote positions often require strong skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch, along with good communication skills. However, some roles may require on-site presence for collaboration or access to specialized hardware.

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.

Which 5 jobs will survive AI?

Remote machine learning roles such as data scientists, AI researchers, machine learning engineers, AI product managers, and AI ethics specialists are expected to persist as AI advances. These jobs require specialized skills in programming, statistical analysis, and domain expertise that are difficult to fully automate. Continuous learning and proficiency in tools like Python, TensorFlow, or PyTorch are essential for these roles.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in competitive markets.

Are ML jobs in demand?

Machine Learning (ML) jobs are in high demand across various industries such as technology, finance, healthcare, and retail. The growth is driven by increasing adoption of AI solutions, data-driven decision making, and the need for expertise in programming, data analysis, and model deployment, making ML a promising career path.

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.

What are popular job titles related to Remote Machine Learning jobs in McLean, VA? For Remote Machine Learning jobs in McLean, VA, the most frequently searched job titles are:
What cities near McLean, VA are hiring for Remote Machine Learning jobs? Cities near McLean, VA with the most Remote Machine Learning job openings:
AI/Machine Learning Engineer

AI/Machine Learning Engineer

Initiate Government Solutions

Washington, DC • Remote

$129K - $155K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Job description

Description

Founded in 2007, Initiate Government Solutions (IGS) is a Woman-Owned Small Business and a fully remote IT services provider supporting federal partners nationwide. We deliver innovative Enterprise IT and Health Services solutions with a strong focus on data analytics, health informatics, cloud migration, AI, and the modernization of federal information systems.


Our vision is to be a health IT trendsetter, continuing to solve the nation's most challenging healthcare IT issues by conceiving, designing, and building solid, creative, and innovative open-source solutions. 


Our mission is to innovate, design, and deliver tailored solutions that balance technical advancement with cost-awareness while providing exceptional service.


IGS is currently pipelining for a remote AI/Machine Learning Engineer to support our work within the federal healthcare industry.  Candidates will be contacted as opportunities become available for further consideration. 


Assignment of Work and Travel:

This is a remote access assignment. The Candidate will work remotely daily and will remotely access VA systems and therein use approved VA provided communications systems. Travel is not required; however, the candidate may be required to attend onsite client meetings as requested.


The AI/Machine Learning Engineer will work alongside a team of highly skilled developers and engineers in the development of AI applications. A motivated and qualified candidate will not only have hands-on development experience in (JavaScript, Python or Java) but also a willingness to collaborate with teams to solve problems. Together we're accelerating our client's digital transformation through the building and deployment of data-driven, scalable AI solutions.


Responsibilities and Duties (Included but not limited to):

  • Design, develop, and deploy machine learning and deep learning models to support clinical decision-making, predictive analytics, and health outcomes research.
  • Fine-tune models for high performance using healthcare-specific data, including EHRs, claims, imaging, and structured/unstructured text.
  • Collaborate with data engineers to clean, preprocess, and normalize healthcare data in compliance with federal data standards (e.g., HL7, FHIR).
  • Build scalable ML pipelines that integrate with federal data platforms and cloud services (e.g., VA's Lighthouse API, Azure Government, AWS GovCloud).
  • Ensure AI/ML solutions meet federal regulations, including HIPAA, FISMA, FedRAMP, and VA Information Security requirements.
  • Implement differential privacy, encryption, and access controls to safeguard sensitive health data.
  • Contribute to the development of governance frameworks to ensure transparent, explainable, and bias-mitigated models.
  • Document model lifecycle, from training to deployment, including risk assessments, validation reports, and audit trails.
  • Work cross-functionally with program managers, clinicians, data scientists, and software developers to identify opportunities for AI/ML applications that improve healthcare delivery and veteran outcomes.
  • Present complex machine learning findings in a way that is actionable and aligned with federal healthcare program goals.
  • Stay updated on the latest developments in AI/ML applications for public health and healthcare operations.
  • Prototype and test emerging AI technologies (e.g., NLP for clinical text, computer vision for imaging diagnostics) for possible integration into government systems.
  • Monitor deployed models for drift, accuracy, and operational effectiveness over time.
  • Maintain model retraining schedules based on new data inputs or policy changes.
  • Prepare comprehensive documentation and reports for internal stakeholders and external oversight (e.g., OMB, GAO, IG audits).
  • Develop dashboards and visualizations to track performance metrics, patient outcomes, and utilization trends impacted by AI/ML tools. 

Requirements

  • Bachelor's degree or higher in one of the following disciplines, Computer Science, Data Science, Artificial Intelligence / Machine Learning, Mathematics / Statistics, Biomedical Engineering, Health Informatics, Electrical or Computer Engineering
  • 4+ years of experience in software and machine learning engineering.
  • Strong knowledge of natural language processing (NLP) and transformer models.
  • 5+ years proficiency in Python and hands-on experience with ML libraries like TensorFlow, PyTorch, or Hugging Face Transformers.
  • Proven experience building scalable, cloud-based AI/ML solutions and enhancing custom question answering mapping/workflows.
  • Expertise in the full ML pipeline, including data processing, model training, serving, and monitoring.
  • Knowledge of NLP architectural strategies such as Retrieval-Augmented Generation, Knowledge Graphs, and Agentic Graphs.
  • Expertise in MLOps best practices, including Infrastructure as Code (IaC), CI/CD pipelines tailored for ML workflows, model version control, and real-time performance monitoring to ensure scalable and reliable AI/ML systems.
  • Familiarity with federal AI governance frameworks and compliance standards (e.g., NIST AI RMF, FedRAMP) is a plus.
  • Passion for developing team-oriented solutions to complex engineering problems 
  • Excellent communication skills and attention to detail
  • Analytical mind and problem-solving aptitude
  • Ability to obtain and maintain a Public Trust
  • Strong organizational skills

Preferred Qualifications and Core Competencies:

  • Master's degree in one of the above-mentioned fields
  • Preferred Tools & Environments: Python, R, TensorFlow, PyTorch, Scikit-learn, AWS (SageMaker), Azure ML, Databricks, Apache Spark, Power BI, Tableau, Plotly, Git, GitHub/GitLab
  • Active VA Public Trust
  • Prior experience supporting a VA program
  • Prior, successful experience working in a remote environment

Successful IGS employees embody the following Core Values:

  • Integrity, Honesty, and Ethics: We conduct our business with the highest level of ethics. Doing things like being accountable for mistakes, accepting helpful criticism, and following through on commitments to ourselves, each other, and our customers. 
  • Empathy, Emotional Intelligence: How we interact with others including peers, colleagues, stakeholders, and customers' matters. We take collective responsibility to create an environment where colleagues and customers feel valued, included, and respected. We work within a diverse, integrated, and collaborative team to drive towards accomplishing the larger mission. We conscientiously and meticulously learn about our customers' and end-users' business drivers and challenges to ensure solutions meet not only technical needs but also support their mission.
  • Strong Work Ethic (Reliability, Dedication, Productivity): We are driven by a strong, self-motivated, and results-driven work ethic. We are reliable, accountable, proactive, and tenacious and will do what it takes to get the job done. 
  • Life-Long Learner (Curious, Perspective, Goal Oriented): We challenge ourselves to continually learn and improve ourselves. We strive to be an expert in our field, continuously honing our craft, and finding solutions where others see problems.

Compensation: There are a host of factors that can influence final salary, including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications.


Benefits: Initiate Government Solutions offers competitive compensation and a robust benefits package, including comprehensive medical, dental, and vision care, matching 401K and profit sharing, paid time off, training time for personal development, flexible spending accounts, employer-paid life insurance, employer-paid short and long term disability coverage, an education assistance program with potential merit increases for obtaining a work-related certification, employee recognition, and referral programs, spot bonuses, and other benefits that help provide financial protection for the employee and their family.


Initiate Government Solutions participates in the Electronic Employment Verification Program.Â