Ai Ml

Ai Ml Developer Jobs

122 jobs found

24d ago

Lead Machine Learning Engineer (Manager IC)

Capital One Richmond, VA

Richmond, VA

24d ago

Full time Manager Agentic Ai Ai Ml

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Job Description

Lead Machine Learning Engineer (Manager IC) in Capital One's Risk Tech group, onsite in Richmond, VA, focusing on designing, deploying, and maintaining AI/ML powered risk management solutions and shaping the long term AI roadmap through cross-functional collaboration.

Responsibilities

Partner with a cross functional team of engineers, data scientists, product managers, and designers to deliver AI driven products that transform how associates operate and deliver value to customers.
Architect, build, validate, deploy, and maintain AI software components driven by ML models, including model evaluation, experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine tune, develop, and evaluate machine learning and foundation models.
Join an Agile, cross functional team to create and enhance software that leverages cutting edge AI and ML capabilities.
Provide thought leadership and technical direction for Capital One's long term AI systems roadmap.
Utilize a broad stack of open source and SaaS AI technologies.
Guide ML infrastructure decisions based on modeling techniques and related considerations.
Retrain, maintain, and monitor production models.
Build optimized data pipelines to feed ML models.
Ensure code quality and security, govern models from a risk perspective, and adhere to Responsible and Explainable AI best practices.

Requirements

Bachelor’s Degree
Minimum 6 years designing and building data intensive solutions using distributed computing (internship experience does not apply)
Minimum 4 years programming in Python, Scala, or Java
Minimum 2 years building, scaling, and optimizing ML systems

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS Bedrock
Google Cloud
Azure
Retrieval Augmented Generation (RAG)

Benefits

Performance-based incentive compensation (cash bonuses and long-term incentives).
Health, financial and other benefits that support total well-being.

The ideal candidate

You love to build systems, take pride in the quality of your work, and are motivated by solving problems that can change banking for good.
You are a skilled communicator, able to explain complex technical concepts to non-technical partners across the business, sometimes in front of large audiences.
You stay current with the latest research and can read scientific publications to judiciously apply novel techniques in production.
You adapt quickly, bring clarity to big, undefined problems, ask questions, and dig deep to uncover root causes, articulating findings concisely; you share new ideas even when unproven.
You are deeply technical with a strong foundation in engineering and mathematics, leveraging hardware, software, and AI knowledge to identify optimization opportunities others miss.
You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unclear.
You maintain a passion for AI research and AI systems, applying novel techniques in production with care.

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24d ago

Lead Machine Learning Engineer

Capital One Richmond, VA

Richmond, VA

24d ago

Full time Agentic Ai Ai Ml Artificial Intelligence

Apply Now

Job Description

Lead Machine Learning Engineer role at Capital One in Risk Tech focuses on designing, deploying, and maintaining AI and ML systems while delivering AI powered products with an emphasis on responsible and explainable AI.

Responsibilities

Collaborate with engineers, data scientists, product managers, and designers to deliver AI powered solutions that improve associates' workflows and customer value.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation, experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine tune, develop, and evaluate machine learning and foundational models.
Work within a cross functional Agile team to build and enhance software that leverages advanced AI and ML capabilities.
Contribute thought leadership and technical vision to the long term AI roadmap at Capital One.
Leverage a broad mix of Open Source and SaaS AI technologies.
Inform ML infrastructure decisions based on an understanding of modeling techniques and associated challenges.
Retrain, maintain, and monitor models in production environments.
Build optimized data pipelines to feed ML models.
Ensure code quality reduces vulnerabilities, maintain model governance from a risk perspective, and follow Responsible and Explainable AI practices.

Requirements

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

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS Bedrock
Google Cloud
Azure
Retrieval Augmented Generation (RAG)

Benefits

Health benefits
Financial benefits
Other benefits
Performance-based incentive compensation (cash bonus(es) and/or long term incentives)

The ideal candidate

You love building systems, take pride in quality, and share a commitment to doing the right thing while tackling problems that can transform banking.
You are a strong communicator who can explain complex technical concepts to non technical partners across the business, including presentations to large audiences.
You stay current with AI research and can interpret scientific publications to apply novel techniques in production.
You adapt quickly, bring clarity to large, undefined problems, ask questions, and dig deep to uncover root causes, articulating findings concisely; you are willing to share new ideas even when unproven.
You are deeply technical with a solid foundation in engineering and mathematics, and you can spot optimization opportunities across hardware, software, and AI.
You are a resilient trailblazer who can forge new paths to meet business goals when the path is unclear.
You maintain a strong appetite for staying current with AI research and systems, applying novel techniques in production in a prudent manner.

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24d ago

Lead Machine Learning Engineer (Manager IC)

Capital One Richmond, VA

Richmond, VA

24d ago

$179k - $205k/yr Full time Manager Ai Ml Artificial Intelligence

Apply Now

Job Description

Capital One Risk Tech is seeking a Lead Machine Learning Engineer who will design, deploy, and maintain AI components and infrastructure that power risk management and AI-enabled products. This onsite role in Richmond, VA blends hands-on engineering leadership with strategic vision to advance Capital One's AI systems and risk controls.

Location

Richmond, VA (onsite)

Compensation

USD 179,400 - 204,700 per year

Responsibilities

Collaborate with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that transform how associates work and provide value to customers.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine-tune, develop, and evaluate machine learning and foundation models.
Work within an Agile, cross-functional team to create and enhance software that leverages state-of-the-art AI and ML capabilities.
Provide thought leadership and technical vision for the long-term roadmap of pioneering AI systems at Capital One.
Utilize a broad stack of Open Source and SaaS AI technologies.
Guide ML infrastructure decisions based on an understanding of ML modeling techniques and related issues.
Retrain, maintain, and monitor models in production.
Build optimized data pipelines to feed ML models.
Ensure code is well-managed to reduce vulnerabilities, keep models well-governed from a risk perspective, and follow responsible and explainable AI practices.

Requirements

Bachelor’s Degree
Minimum of six years designing and building data-intensive solutions on distributed computing platforms (internships excluded)
Minimum of four years programming in Python, Scala, or Java
Minimum of two years building, scaling, and optimizing ML systems

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS Bedrock
Google Cloud
Azure

Benefits

Health, financial and other benefits that support your total well-being
Performance-based incentive compensation (cash bonuses and/or long term incentives)

The ideal candidate

You love to build systems, take pride in the quality of your work, and aim to contribute to banking improvements that matter.
You are a strong communicator who can explain complex technical concepts to non-technical partners across the business, including presentations to large audiences.
You stay current with AI research and can interpret scientific publications to judiciously apply novel techniques in production.
You adapt quickly and bring clarity to big, undefined problems, asking probing questions and articulating findings concisely, with the courage to propose new ideas even if unproven.
You are deeply technical, with a solid foundation in engineering and mathematics, and an ability to see and exploit optimization opportunities across hardware, software, and AI.
You are a resilient trailblazer who can forge new paths to achieve business goals when the route is uncertain.
You maintain a passion for the latest AI research and systems, applying novel techniques in production with careful consideration.

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24d ago

Lead Machine Learning Engineer (Manager IC)

Capital One McLean, VA

McLean, VA

24d ago

Full time Manager Ai Ml Artificial Intelligence

Apply Now

Job Description

Capital One seeks a Lead Machine Learning Engineer (Manager IC) to sit onsite in McLean, VA. This role designs, deploys, and sustains AI powered software and ML systems across Risk Tech, collaborating with cross-functional teams and shaping the long-term AI roadmap.

Responsibilities

Collaborate with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI powered products that transform associates' workflows and deliver value to customers.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability, and agentic AI.
Fine-tune, develop, and evaluate machine learning and foundation models.
Work as part of an Agile, cross-functional team to create software that leverages state-of-the-art AI and ML capabilities.
Contribute thought leadership and technical vision to the long-term roadmap of pioneering AI systems at Capital One.
Leverage a broad stack of Open Source and SaaS AI technologies.
Inform ML infrastructure decisions with an understanding of ML modeling techniques and related challenges.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
Ensure code quality minimizes vulnerabilities, maintains model governance, and aligns with Responsible and Explainable AI practices.

Requirements

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.

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
Retrieval Augmented Generation (RAG)
AWS Bedrock
Google Cloud
Azure

Benefits

Performance-based incentive compensation (cash bonus and/or long term incentives)
Health benefits
Financial benefits

The Ideal Candidate

You enjoy building robust systems, take pride in quality, and are motivated to do the right thing while solving banking challenges.
You communicate clearly, translating complex technical concepts to non-technical partners across the business, including presentations to larger audiences.
You stay current with AI research and can translate publications into production-ready approaches.
You adapt quickly, bring clarity to ambiguous problems, ask insightful questions, and share new ideas with confidence.
You have a solid engineering and mathematical foundation, and you leverage expertise across hardware, software, and AI to spot optimization opportunities.
You are a resilient trailblazer who can chart new paths to achieve business goals when the route is not obvious.
You maintain a passion for AI research and systems, applying novel approaches judiciously in production.
Strategic and business oriented: think beyond technology, deeply understand business needs and how AI can solve them; you strategize and prioritize work to deliver maximum business value.
Highly collaborative and transparent: partner across engineering, product, and data science; communicate progress and blockers openly; share knowledge for the team's success.
Technically mature and humble: strong engineering and math foundation; resilient problem solver; articulate findings succinctly; commit to team decisions.
Flexible and fungible: willing to contribute across the tech stack and adapt to shifting priorities.
A lifelong learner: stay current with AI research and apply novel techniques judiciously with focus on business impact.

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24d ago

Senior Machine Learning Engineer (AI Foundations)

Capital One McLean, VA

McLean, VA

24d ago

$162k - $185k/yr Full time Ai Ml Artificial Intelligence Big Data

Apply Now

Job Description

Benefits at Capital One include health benefits, financial benefits, and performance-based incentive compensation. This onsite Senior Machine Learning Engineer role in McLean, VA offers the opportunity to work on productionizing ML applications at scale, with exposure to the latest ML engineering practices. Salary ranges from USD 161,800 to 184,600 per year.

Senior Machine Learning Engineer (AI Foundations) is part of an Agile team focused on productionizing ML applications at scale. The role emphasizes ML architectural design, developing and reviewing model and application code, and ensuring high availability and performance of ML systems.

Responsibilities

Design, build, and deliver ML models and components that address real-world business needs, partnering with Product and Data Science teams.
Inform ML infrastructure decisions by applying knowledge of modeling techniques, data, feature selection, model training, hyperparameters, dimensionality, bias/variance, and validation.
Tackle complex challenges by writing and testing application code, developing and validating ML models, and automating tests and deployment.
Collaborate within a cross-functional Agile team to create software enabling state-of-the-art big data and ML applications.
Retrain, maintain, and monitor models in production.
Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
Construct optimized data pipelines to feed ML models.
Apply continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code.
Ensure code is well-managed to reduce vulnerabilities, with models governed from a risk perspective and aligned with Responsible and Explainable AI principles.
Use programming languages such as Python, Scala, or Java.

Requirements

Bachelor’s Degree
At least 4 years of experience programming with Python, Scala, or Java (Internship experience does not apply)
At least 3 years of experience designing and building data-intensive solutions using distributed computing
At least 2 years of on-the-job experience with an industry-recognized ML framework (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
At least 1 year of experience productionizing, monitoring, and maintaining models

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow

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24d ago

Senior Machine Learning Engineer (AI Foundations)

Capital One New York, NY

New York, NY

24d ago

$177k - $201k/yr Full time Ai Ml Artificial Intelligence Big Data

Apply Now

Job Description

What you get

Join Capital One on the AI Foundations team, where the focus is on productionizing machine learning at scale, crafting resilient architectures, and delivering high-performance ML systems. This onsite role in New York, NY combines a competitive salary with comprehensive health and financial benefits, plus incentives tied to performance. You’ll collaborate across product and data science teams, contribute to responsible and explainable AI practices, and grow your expertise through end-to-end ML engineering work.

Salary: USD 176,500 - 201,400 per year
Location: New York, NY — onsite
Benefits: Health benefits
Financial benefits: Financial benefits
Incentives: Performance-based incentive compensation (cash bonuses and/or long-term incentives)
Education: Bachelor’s Degree

What you'll do

Develop and deploy ML models and components that address real world business needs, partnering with Product and Data Science teams
Guide ML infrastructure decisions using knowledge of modeling techniques, data choices, feature selection, training, hyperparameters, bias/variance, and validation
Tackle complex problems by writing and testing application code, building and validating ML models, and automating tests and deployment
Work within a cross functional Agile team to create software that powers advanced big data and ML applications
Retrain, maintain, and monitor models in production environments
Utilize or build cloud based architectures and platforms to deliver optimized ML models at scale
Design efficient data pipelines to feed ML models
Apply CI/CD best practices, including test automation and monitoring, to ensure reliable deployment of ML models and code
Maintain secure, well-governed code and follow responsible and explainable AI practices
Proficiency in Python, Scala, or Java

Basic qualifications

Bachelor’s Degree
At least 4 years of professional experience coding with Python, Scala, or Java (internships excluded)
At least 3 years of designing and building data intensive solutions using distributed computing
At least 2 years of hands-on experience with ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow)
At least 1 year of experience productionizing, monitoring, and maintaining models

Preferred qualifications

1+ years of experience building, scaling, and optimizing ML systems
1+ years of experience gathering and preparing data for ML models
2+ years of delivering performant, resilient, and maintainable code
Experience developing and deploying ML solutions in AWS, Azure, or Google Cloud Platform
Master's or doctoral degree in computer science, electrical engineering, mathematics, or a related field
3+ years of experience with distributed file systems or multi-node database paradigms
Contributed to open source ML software
Authored or co-authored a paper on a ML technique, model, or concept
3+ years building production-ready data pipelines that feed ML models
Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
Experience using interactive AI tooling to accelerate productivity beyond basic code completion

Technologies

Python, Scala, Java
scikit-learn, PyTorch, Dask, Spark, TensorFlow
AWS, Azure, Google Cloud Platform

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24d ago

Sr. Lead Machine Learning Engineer

Capital One McLean, VA

McLean, VA

24d ago

$230k - $262k/yr Full time Ai Ml Big Data Data Science

Apply Now

Job Description

Capital One is seeking a Sr Lead Machine Learning Engineer for an onsite role in McLean, VA. The position offers a competitive salary range of USD 229,900 - 262,400 per year, comprehensive health and financial benefits, and performance-based incentives. You will join an Agile team focused on designing, developing, and productionizing scalable ML applications and architectures, collaborating with Product and Data Science teams to drive real-world impact while ensuring high availability and performance.

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation (cash bonuses and/or long-term incentives)

Responsibilities

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

Technologies

Python
Scala
Java
scikit-learn
PyTorch
Dask
Spark
TensorFlow
AWS
Azure
Google Cloud Platform

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