As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning and NLP models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning and NLP models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning and NLP models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning and NLP models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Machine learning * Analysis and management of large datasets (>1M records) Preferred Qualifications ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Machine learning * Analysis and management of large datasets (>1M records) Preferred Qualifications ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
Principal Associate, Data Scientist - Retail Bank Valuations Data Science
Mclean, VA · On-site
$59K - $60K/yr
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
Principal Associate, Data Scientist - Retail Bank Valuations Data Science
Mclean, VA · On-site
$59K - $60K/yr
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models through all phases of development, from design through training ...
Associate Data Scientist
Washington, DC · On-site
$66K - $67K/yr
You are excited to work at a fast-paced startup where you will have a chance to expand your ... Training machine learning models to solve complex problems. * Productionizing models in a Scala ...
Associate Data Scientist
Washington, DC · On-site
$66K - $67K/yr
You are excited to work at a fast-paced startup where you will have a chance to expand your ... Training machine learning models to solve complex problems. * Productionizing models in a Scala ...
Associate Data Scientist
Washington, DC · On-site
$66K - $67K/yr
You are excited to work at a fast-paced startup where you will have a chance to expand your ... Training machine learning models to solve complex problems. * Productionizing models in a Scala ...
Associate Data Scientist
Washington, DC · On-site
$66K - $67K/yr
You are excited to work at a fast-paced startup where you will have a chance to expand your ... Training machine learning models to solve complex problems. * Productionizing models in a Scala ...
Forward Deployed AI Engineer
Mclean, VA · On-site
Startup experience or another clear record of independently owning and delivering technical projects is preferred * Experience with distributed systems, machine learning infrastructure, or ...
Quick apply
Forward Deployed AI Engineer
Mclean, VA · On-site
Startup experience or another clear record of independently owning and delivering technical projects is preferred * Experience with distributed systems, machine learning infrastructure, or ...
Applied AI Scientist
Washington, DC · On-site
Required : • Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Data ... fast-paced, startup environment Company : Valiant Harbor International, founded in 2013, is a ...
Applied AI Scientist
Washington, DC · On-site
Required : • Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Data ... fast-paced, startup environment Company : Valiant Harbor International, founded in 2013, is a ...
An early-stage defense AI startup building autonomous AI agents for national security and federal ... Experience with AI/LLMs, agentic AI systems, or machine learning platforms * Familiarity with ...
An early-stage defense AI startup building autonomous AI agents for national security and federal ... Experience with AI/LLMs, agentic AI systems, or machine learning platforms * Familiarity with ...
An early-stage defense AI startup building autonomous AI agents for national security and federal ... Experience with AI/LLMs, agentic AI systems, or machine learning platforms * Familiarity with ...
An early-stage defense AI startup building autonomous AI agents for national security and federal ... Experience with AI/LLMs, agentic AI systems, or machine learning platforms * Familiarity with ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build statistical and machine learning models to challenge the models in production * Flex your ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build statistical and machine learning models to challenge the models in production * Flex your ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models to challenge "champion models" that are deployed in production today ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models to challenge "champion models" that are deployed in production today ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Audit machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Audit machine learning models through all phases of development, from design through training ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Optimize and deploy machine learning models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Optimize and deploy machine learning models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models to challenge "champion models" that are deployed in production today ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Build machine learning models to challenge "champion models" that are deployed in production today ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Optimize and deploy machine learning models through all phases of development, from design through ...
As a startup, we disrupted the credit card industry by individually personalizing every credit card ... Optimize and deploy machine learning models through all phases of development, from design through ...
Machine Learning Startup information
See Washington, DC salary details
$28.9K - $35.3K
5% of jobs
$37.5K is the 25th percentile. Wages below this are outliers.
$35.3K - $41.8K
59% of jobs
$41.8K - $48.2K
9% of jobs
$48.7K is the 75th percentile. Wages above this are outliers.
$48.2K - $54.6K
17% of jobs
$54.6K - $61.1K
4% of jobs
$61.1K - $67.5K
2% of jobs
$67.5K - $73.9K
3% of jobs
$73.9K - $80.4K
0% of jobs
$80.4K - $86.8K
0% of jobs
$86.8K - $93.2K
0% of jobs
$93.2K - $99.7K
0% of jobs
$28.9K
$48.2K
$99.7K
How much do machine learning startup jobs pay per year?
As of Aug 6, 2026, the average yearly pay for machine learning startup 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 the key skills and qualifications needed to thrive in a machine learning startup, and why are they important?
To succeed in a Machine Learning Startup, a strong background in computer science, statistics, and applied mathematics is essential, along with practical experience building and deploying machine learning models. Proficiency in tools such as Python, TensorFlow, PyTorch, and cloud-based platforms, as well as familiarity with data versioning and model deployment systems, is highly valuable. Adaptability, entrepreneurial thinking, and strong communication skills are crucial for thriving in the dynamic startup environment. These competencies enable effective product development, rapid iteration, and impactful collaboration within a fast-paced, resource-constrained setting.
What are the typical responsibilities and daily challenges when working at a machine learning startup?
At a Machine Learning Startup, your daily tasks often include collecting and preprocessing data, training and validating models, collaborating with engineers to deploy solutions, and iterating rapidly based on feedback and performance metrics. You may also contribute to brainstorming sessions, product roadmapping, and customer discovery processes. Common challenges include working with limited labeled data, balancing research with production needs, and managing shifting priorities as the business pivots or scales. This dynamic environment provides a valuable opportunity to make a tangible impact, develop a broad skill set, and gain exposure to multiple aspects of both technology and entrepreneurship.
What is a machine learning startup?
A Machine Learning Startup job typically involves working in a fast-paced, early-stage company focused on developing and applying machine learning technologies. Employees may take on diverse responsibilities, including data collection, model development, algorithm optimization, and deployment. Since startups require adaptability, roles often blend research, engineering, and business-oriented problem-solving. These positions offer opportunities to work on cutting-edge innovations but may also demand long hours and rapid prototyping.
What are the most commonly searched types of Machine Learning Startup jobs in Washington, DC? The most popular types of Machine Learning Startup jobs in Washington, DC are:
What are popular job titles related to Machine Learning Startup jobs in Washington, DC? For Machine Learning Startup jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Startup jobs in Washington, DC look for? The top searched job categories for Machine Learning Startup jobs in Washington, DC are:
Full-time
Re-posted 8 days ago
Capital One rating
7.7
Based on 146 frontline employees who took The Breakroom Quiz
93rd of 170 rated banks
Job description
Director, Data Scientist - Generative AI Systems
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
The Generative AI Systems (Genesis) team within Card Data Science builds state-of-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time-series sequencing modeling. We partner with product, tech and design teams to deliver internal applications based on these solutions that drive efficiency in our business and data analytics teams, as well as customer-facing applications that enhance the customer experience. You will lead a seasoned group of natural language processing (NLP), speech, and computer vision specialists, experimenting with emerging technologies in generative AI, delivering software implementing these technologies, and contributing research to major NLP and AI/ML conferences.
Role Description
In this role, you will:
The Ideal Candidate is:
Basic Qualifications:
Preferred Qualifications:
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: $269,100 - $307,200 for Dir, Data Science
New York, NY: $293,600 - $335,100 for Dir, Data Science
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).
Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.
As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
Team Description
The Generative AI Systems (Genesis) team within Card Data Science builds state-of-art, generative AI-based solutions for dialogue, text summarization, reading comprehension, speech recognition, image/document processing as well as time-series sequencing modeling. We partner with product, tech and design teams to deliver internal applications based on these solutions that drive efficiency in our business and data analytics teams, as well as customer-facing applications that enhance the customer experience. You will lead a seasoned group of natural language processing (NLP), speech, and computer vision specialists, experimenting with emerging technologies in generative AI, delivering software implementing these technologies, and contributing research to major NLP and AI/ML conferences.
Role Description
In this role, you will:
- Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money.
- Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data.
- Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.
- Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals.
The Ideal Candidate is:
- Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.
- Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
- A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
- Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Basic Qualifications:
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date :
- A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
- A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
- A PHD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 4 years of experience performing data analytics
- At least 4 years of experience leveraging open source programming languages for large scale data analysis
- At least 4 years of experience working with machine learning
- At least 4 years of experience utilizing relational databases
Preferred Qualifications:
- PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
- At least 1 year of experience working with AWS
- At least 3 years of experience managing people
- At least 5 years of experience in Python, Scala, or R for large scale data analysis
- At least 5 years of experience with machine learning
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: $269,100 - $307,200 for Dir, Data Science
New York, NY: $293,600 - $335,100 for Dir, Data Science
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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