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Remote Machine Learning Finance Jobs in Washington

Capital One

Sr Lead Machine Learning Engineer

Mclean, VA · On-site +1

Sr Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other ...

Capital One

Sr. Lead Machine Learning Engineer (IC)

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be ... Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other ...

Maximus

Data Scientist (Remote)

VA · On-site +1

Build Your Financial Future - Take advantage of our 401(k) Retirement Savings Plan with Company ... NLP, and machine learning (both supervised and unsupervised) to improve relevance and ...

Comcast

Engineer 6, Machine Learning, Data & AI

Reston, VA · On-site +1

$119K - $143K/yr

... remote option.) Job Summary We are seeking a visionary Senior Technologist, Data & Agentic AI ... physically, financially and emotionally through the big milestones and in your everyday life.

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Remote Machine Learning Finance information

What is a remote machine learning finance professional?

A Remote Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems, often from a remote location. Professionals in this field develop models to predict market trends, assess risks, automate trading, or detect fraud using large datasets. Remote roles allow employees to work from anywhere, collaborating with teams virtually and using cloud-based tools to analyze data. These positions typically require strong programming skills, knowledge of finance, and experience with machine learning frameworks.

How do remote machine learning finance professionals typically collaborate with cross-functional teams?

Remote machine learning professionals in finance often work closely with data analysts, financial experts, and software engineers to develop and deploy predictive models. Collaboration is typically facilitated through virtual meetings, shared documentation, and project management tools. Clear communication and regular check-ins are crucial for aligning goals and ensuring that machine learning solutions address real business needs. Many organizations also encourage participation in virtual workshops and code reviews to maintain a strong sense of teamwork despite the remote setting.

What are the key skills and qualifications needed to thrive as a remote machine learning finance professional?

To excel in Remote Machine Learning Finance, strong analytical skills, a solid background in statistics or mathematics, and experience with financial data are essential, often supported by a degree in computer science, finance, or a related field. Familiarity with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or Scikit-learn), and knowledge of financial modeling tools are typically required. Excellent problem-solving, communication, and the ability to work independently are standout soft skills in this remote environment. These abilities are crucial for developing effective financial models, interpreting complex data, and collaborating with distributed teams to drive business value.

What are the most commonly searched types of Machine Learning Finance jobs in Washington?

The most popular types of Machine Learning Finance jobs in Washington are:

What are popular job titles related to Remote Machine Learning Finance jobs in Washington?

For Remote Machine Learning Finance jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Finance jobs in Washington look for?

The top searched job categories for Remote Machine Learning Finance jobs in Washington are:

What cities in Washington are hiring for Remote Machine Learning Finance jobs?

Cities in Washington with the most Remote Machine Learning Finance job openings:

Remote Machine Learning Finance jobs near you

Sr Lead Machine Learning Engineer

Capital One

Mclean, VA • On-site, Remote

Full-time

Re-posted 12 days ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

93rd of 171 rated banks

Job description

Sr Lead Machine Learning Engineer
Job Description

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:

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 8 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 3 years of experience building, scaling, and optimizing ML systems

  • At least 2 years of experience leading teams developing ML solutions 

Preferred Qualifications:

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

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

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

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

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

  • 3+ years of people management experience 

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

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

  • Ability to communicate complex technical concepts clearly to a variety of audiences 

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

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.

McLean, VA: $229,900 - $262,400 for Sr. 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 the Capital 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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