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Machine Learning Contract Remote Jobs in Washington, DC

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 ...

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 ...

Senior AI/ML Engineer

Great Falls, VA · Remote

$105K - $145K/yr

Location: Vienna VA (We will consider Remote candidates within US Mainland on EST) Required ... Experience with machine learning and deep learning frameworks such as TensorFlow, PyTorch, and ...

Solution Engineer

Herndon, VA · Remote

$179K - $318K/yr

This role heavily emphasizes structural data integrity, deep machine learning pipelines, and robust ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

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Machine Learning Contract Remote information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do machine learning contract remote jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning contract remote in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

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

Remote machine learning contractors often face challenges such as managing communication across time zones, accessing necessary data securely, and staying aligned with the client's project expectations. To address these, it’s important to establish clear communication channels, use secure data transfer protocols, and schedule regular check-ins with project stakeholders. Building strong documentation habits and leveraging collaborative tools like version control or shared notebooks can also help ensure smooth workflow and project transparency.

What are the key skills and qualifications needed to thrive as a Machine Learning Contractor in a remote role, and why are they important?

To thrive as a Machine Learning Contractor working remotely, you need strong proficiency in mathematics, programming (typically Python), and a solid understanding of machine learning algorithms, usually supported by a relevant degree or equivalent experience. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and cloud platforms such as AWS or Azure is essential, as well as experience with version control systems like Git. Excellent self-motivation, time management, and communication skills help you effectively collaborate with distributed teams and manage multiple projects independently. These competencies are crucial for delivering high-quality, scalable solutions and meeting client expectations in a flexible, remote work environment.

What are machine learning contract remote jobs?

Machine learning contract remote jobs are temporary work opportunities where professionals use machine learning techniques to solve problems for organizations, but do so remotely, often from home or another location. These roles typically involve building, training, and deploying models, analyzing data, and collaborating with teams virtually. Contracts can vary in length and scope, allowing flexibility for both the employer and the worker. These positions are ideal for individuals seeking project-based work or more flexible schedules, and require strong technical skills and the ability to communicate effectively online.

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

AspectMachine Learning Contract RemoteData Scientist Contract Remote
Required CredentialsDegree in Computer Science, Data Science, or related field; experience with ML frameworksDegree in Statistics, Data Science, or related; proficiency in data analysis tools
Work EnvironmentRemote, project-based, often collaborative with ML engineersRemote, analytical, often cross-functional teams
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting
Common Search & ComparisonYesYes

Machine Learning Contract Remote roles focus on developing and deploying ML models, requiring specialized skills in algorithms and frameworks. Data Scientist Contract Remote positions emphasize data analysis, statistical modeling, and insights generation. While both roles often work remotely and share similar credentials, their core responsibilities differ, making this comparison useful for job seekers exploring related opportunities.

What are the most commonly searched types of Machine Learning Remote jobs in Washington, DC? The most popular types of Machine Learning Remote jobs in Washington, DC are:
What are popular job titles related to Machine Learning Contract Remote jobs in Washington, DC? For Machine Learning Contract Remote jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Contract Remote jobs in Washington, DC look for? The top searched job categories for Machine Learning Contract Remote jobs in Washington, DC are:
Infographic showing various Machine Learning Contract Remote job openings in Washington, DC as of July 2026, with employment types broken down into 1% As Needed, 62% Full Time, 22% Part Time, 1% Temporary, and 14% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $48,230 per year, or $23.2 per hour.
Sr. Director, Machine Learning Engineering (Remote-Eligible)

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Capital One

Mclean, VA • On-site, Remote

$255K/yr

Full-time

Posted 6 days ago


Capital One rating

7.8

Company rating: 7.8 out of 10

Based on 143 frontline employees who took The Breakroom Quiz

76th of 149 rated banks


Job description

Sr. Director, Machine Learning Engineering (Remote-Eligible)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One's consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale - turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org's mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment.

What you'll do in the role:

  • Lead and scale a high-performing engineering organization responsible for the Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across Capital One products and services.

  • Define the technical strategy, delivery roadmap, and operating model for a portfolio spanning recommendation systems, ranking, decisioning, GenAI infrastructure, MLOps, and low-latency application-serving systems

  • Build, develop, and manage engineers and engineering leaders; set a high bar for hiring, performance, talent density, coaching, and succession planning across the organization

  • Partner cross-functionally with Product, Data Science, Cloud Infrastructure, and Machine Learning Platform teams to align strategy, prioritize investments, and co-develop advanced recommendation systems and algorithms serving Capital One users

  • Drive the design, buildout, and operation of robust ML infrastructure and pipelines supporting feature extraction, model training, testing, guardrails, evaluation, deployment, and both real-time and batch inference with strong reliability, scalability, and operational rigor

  • Architect low-latency, event-driven systems for real-time personalization and decisioning based on streaming data, user behavior, and contextual signals

  • Drive the evolution of MLOps practices through automated, metrics-backed deployment workflows, validation and testing systems, model lifecycle governance, and scalable observability

  • Guide the adoption of state-of-the-art AI and LLM optimization techniques to improve scalability, cost, latency, throughput, and reliability of large-scale production AI systems

  • Provide organizational technical and people leadership by influencing architecture, engineering standards, delivery excellence, incident management, and cross-team strategy while mentoring managers, tech leads, and senior engineers.

  • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

  • Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI.

Capital One is open to hiring a Remote Employee for this opportunity.

Basic Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing or leading AI and ML algorithms or technologies

  • At least 5 years of people leadership experience

Preferred Qualifications:

  • 7 years of experience managing and leading an engineering team

  • 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure)

  • Master's or PhD in Computer Science or a relevant technical field
    Proven expertise designing, implementing, and scaling personalization platforms and recommendation systems across feed personalization, ads ranking, or targeted marketing messaging

  • Proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow)

  • Experience optimizing large-scale training and inference systems for hardware utilization, latency, throughput, and cost

  • Deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment
    Deep experience with MLOps, model observability, and production ML lifecycle management

  • Strong track record building organizations, developing managers and senior engineers, and leading through scale and ambiguity
    Excellent communication and presentation skills, with the ability to influence senior stakeholders and articulate complex AI concepts clearly

  • Proven leadership in driving platform strategy, cross-functional execution, and technical direction across a large organization

  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Remote (Regardless of Location): $286,200 - $326,700 for Sr. Dir, Machine Learning Engineering


McLean, VA: $314,800 - $359,300 for Sr. Dir, Machine Learning Engineering










Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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