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Manager Remote Machine Learning Engineer Jobs in Washington

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103.60K - $136.50K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk ...

Machine Learning Engineer - Remote

Vienna, VA · Remote

$114.90K - $138K/yr

Monitor production models for accuracy, drift, and latency; manage retraining schedules. Data ... Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong ...

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Monitor production models for accuracy, drift, and latency; manage retraining schedules. Data ... Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong ...

Senior Machine Learning Engineer

Washington, DC · Remote

$118.40K - $162.50K/yr

Overview Senior Machine Learning Engineer at GiveCampusLocationWashington, DC (Remote)Salary$118.40K - $162.50K/yr (Estimated pay)TypeFull-timePosted1 hour agoAbout GiveCampusGiveCampus is the world ...

We offer flexibility to help you manage your work-life balance effectively. * Remote Work: Niyam ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

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Manager Remote Machine Learning Engineer information

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

To thrive as a Manager Remote Machine Learning Engineer, strong expertise in machine learning algorithms, programming (Python, R), and a degree in computer science or a related field are essential, along with proven leadership experience. Familiarity with cloud platforms (AWS, Azure, GCP), ML frameworks (TensorFlow, PyTorch), and project management tools is typically required, as well as certifications such as AWS Certified Machine Learning or Google Professional Machine Learning Engineer. Outstanding communication, team leadership, and problem-solving skills help foster collaboration and drive remote teams toward project goals. These capabilities are vital for effectively managing distributed teams, delivering robust AI solutions, and ensuring project success in a remote environment.

How does a Manager Remote Machine Learning Engineer typically balance team leadership with hands-on technical responsibilities?

A Manager Remote Machine Learning Engineer often splits time between leading and mentoring a distributed team and actively contributing to machine learning projects. While overseeing project timelines, conducting code reviews, and setting technical direction are key leadership tasks, managers also stay involved in model development and troubleshooting to maintain technical expertise. Effective communication and clear documentation are crucial, as remote teams rely on these to collaborate efficiently across different time zones. Balancing these responsibilities requires strong organizational skills and the ability to prioritize both people management and technical deliverables.

What is a Manager Remote Machine Learning Engineer?

A Manager Remote Machine Learning Engineer is a leadership role responsible for overseeing a team of machine learning engineers who work remotely. They manage the development, deployment, and optimization of machine learning models and ensure that projects align with organizational goals. In addition to technical expertise, this manager focuses on remote team collaboration, communication, and productivity. They often coordinate workflows, mentor team members, and act as a bridge between technical teams and business stakeholders.

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

AspectManager Remote Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML engineeringBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRemote, collaborative teams, focus on ML model deploymentRemote or on-site, data analysis, model development, research
Employer & Industry UsageTech companies, AI startups, large enterprisesTech, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding managerial roles in ML teamsData analysis, modeling, research tasks

The Manager Remote Machine Learning Engineer oversees ML projects and teams, focusing on deployment and management, while Data Scientists primarily analyze data and develop models. Both roles require strong technical skills, but the manager role emphasizes leadership and project oversight.

What are the most commonly searched types of Remote Machine Learning Engineer jobs in Washington? The most popular types of Remote Machine Learning Engineer jobs in Washington are:
What are popular job titles related to Manager Remote Machine Learning Engineer jobs in Washington? For Manager Remote Machine Learning Engineer jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Manager Remote Machine Learning Engineer jobs? Cities in Washington with the most Manager Remote Machine Learning Engineer job openings:
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Capital One

Mclean, VA • On-site, Remote

$103.60K - $136.50K/yr

Full-time

Posted 26 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

74th of 141 rated banks


Job description

Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You'll participate in the detailed technical design, development, and implementation of machine learning applications using existing and emerging technology platforms. You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have the opportunity to continuously learn and apply the latest innovations and best practices in machine learning engineering.

What you'll do in the role:

The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following:

  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams

  • Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation)

  • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment

  • Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications

  • Retrain, maintain, and monitor models in production

  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.

  • Construct optimized data pipelines to feed ML models

  • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code

  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI

  • Use programming languages like Python, Scala, or Java

Basic Qualifications:

  • Bachelor's Degree

  • At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)

  • At least 4 years of experience programming with Python, Scala, or Java

  • At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications:

  • Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field

  • 3+ years of experience building production-ready data pipelines that feed ML models

  • 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow

  • 2+ years of experience developing performant, resilient, and maintainable code

  • 2+ years of experience with data gathering and preparation for ML models

  • 2+ years of people leader experience

  • 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation

  • Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform

  • Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance

  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents

  • Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion

At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer).

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.

McLean, VA: $197,300 - $225,100 for Lead Machine Learning Engineer











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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