Technical Lead

Technical Lead Data Jobs

138 jobs found

21d ago

Lead Machine Learning Engineer-MLOps

JPMorganChase Palo Alto, CA

Palo Alto, CA

21d ago

$164k - $260k/yr Full time Manager Ai Ml Artificial Intelligence

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Job Description

Join JPMorgan Chase as a Lead Machine Learning Engineer MLOps on the Recommendation Engine team, working onsite in Palo Alto, CA. You will build and deploy ML models using a modern MLOps stack, spanning distributed training on GPU clusters, real-time and batch inference, and scalable hyperparameter tuning with production-grade validation. The role offers a competitive base salary in the range of USD 164,350 to 260,000 per year.

Responsibilities

Design, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters to enable scalable ML workflows.
Develop pipelines for high throughput real time as well as batch inference, prioritizing performance and reliability.
Implement quantization techniques and deploy large language models to improve efficiency across specific GPU architectures.
Oversee the management and optimization of vector databases to support advanced AI and ML applications.
Establish and maintain comprehensive monitoring and observability pipelines to ensure system health, performance, and rapid issue resolution.
Collaborate with product, architecture, and other engineering teams to integrate new technologies and continuously improve existing infrastructure.
Partner with cross functional teams to define scalable and performant technical solutions.

Requirements

BS in Computer Science or related Engineering field with 6+ years of experience.
MS in Computer Science or related Engineering field with 4+ years of experience.
Strong proficiency in Python and cloud computing, preferably AWS.
Understanding of quantization techniques such as PTQ and AWQ used to accelerate LLM inference on specific GPU architectures.
Experience in systems engineering fundamentals including caching, CUDA, autoscaling, high throughput, low latency, and cross-region resilience.
Solid knowledge and passion for data science fundamentals, including training and deploying models.
Experience with monitoring and observability tools to track model inputs/outputs and feature statistics.
Operational experience with big data and ML tools such as Ray, DuckDB, Spark, and with training/inference systems like Ray and vllm/SGLang.
Strong engineering fundamentals and an analytical mindset.

Technologies

Python
AWS
CUDA
PTQ
AWQ
Ray
DuckDB
Spark
vllm
SGLang
Docker
Kubernetes
ECS
Airflow
Kubeflow
Vector databases

Benefits

Base salary determined by role, experience, skills, and location.
Commission-based pay and discretionary incentive compensation, paid in cash and/or equity, recognizing individual contributions.
Comprehensive health care coverage.
On site health and wellness centers.
Retirement savings plan.
Backup childcare.
Tuition reimbursement.
Mental health support.
Financial coaching.

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22d ago

Lead Machine Learning Engineer (Manager IC)

Capital One Richmond, VA

Richmond, VA

22d ago

Full time Manager Agentic Ai Ai Ml

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Job Description

Benefits

Capital One offers a competitive rewards package and a focus on total well-being, including incentives and benefits that support your career and life goals.

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

Location: Richmond, VA, onsite.

Responsibilities

Collaborate with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI powered products that change how our associates work and provide value to our customers.
Design, develop, test, deploy, and support AI software components utilizing 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.
Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes 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 your ML infrastructure decisions using your understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
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.

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)

The ideal candidate

You love to build systems, take pride in the quality of your work, and are motivated to make banking better.
You are a skilled communicator, comfortable explaining complex technical concepts to non-technical partners across the business, sometimes in front of large audiences.
You stay current with AI research and can interpret scientific publications to judiciously apply novel techniques in production.
You adapt quickly, bring clarity to big, undefined problems, ask questions, dig deep, and articulate findings concisely with the courage to share new ideas, even if unproven.
You are deeply technical, with a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to spot optimization opportunities others miss.
You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
You maintain a passion for AI research and AI systems, and apply novel techniques in production with care.

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22d ago

Lead Machine Learning Engineer

Capital One Richmond, VA

Richmond, VA

22d ago

Full time Agentic Ai Ai Ml Artificial Intelligence

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Job Description

Benefits

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

This onsite opportunity in Richmond, VA supports collaborative, impact-driven work in Capital One's Risk Tech group, with a focus on responsible and explainable AI and opportunities to deliver AI powered products that matter for associates and customers.

Responsibilities

Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI powered products that transform how associates work 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.
Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes 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 using an understanding of ML modeling techniques and issues.
Retrain, maintain, and monitor models in production.
Construct optimized data pipelines to feed ML models.
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.

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

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22d ago

Lead Machine Learning Engineer (Manager IC)

Capital One Richmond, VA

Richmond, VA

22d ago

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

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Job Description

Capital One Risk Tech is seeking a Lead Machine Learning Engineer (Manager IC) to architect, deploy, and sustain AI and ML capabilities that underpin risk management and AI-powered products. This onsite role in Richmond, Virginia offers a salary range of USD 179,400 to 204,700 per year and requires a bachelor’s degree along with extensive experience building data-intensive solutions and ML systems.

Responsibilities

Collaborate with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-driven products that improve how associates work and create value for customers.
Design, develop, test, deploy, and support AI software components that use 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 foundation models.
Work within an Agile, cross-functional team to build and enhance software leveraging state-of-the-art AI and ML capabilities.
Contribute thought leadership and technical vision to the long-term roadmap for pioneering AI systems at Capital One.
Utilize a broad mix of Open Source and SaaS AI technologies.
Make informed ML infrastructure decisions grounded in modeling techniques and related considerations.
Retrain, maintain, and monitor models in production environments.
Build optimized data pipelines to feed machine learning models.
Ensure code quality and governance, manage risk by following responsible and explainable AI practices.

Requirements

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing (internships do not count)
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

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

Has a passion for building systems, takes pride in code quality, and aims to contribute to meaningful banking innovations.
Is a strong communicator, able to explain complex technical concepts to non-technical partners across the business, including presenting to large audiences when needed.
Keeps up with the latest research, and can interpret scientific publications to judiciously apply novel techniques in production.
Adapts quickly, brings clarity to undefined problems, asks questions, digs deep to uncover root causes, and communicates findings succinctly. Willing to share new ideas even if unproven.
Is deeply technical with a solid foundation in engineering and mathematics, and can leverage hardware, software, and AI know-how to spot optimization opportunities.
Demonstrates resilience and the ability to forge new paths to achieve business goals when routes are unclear.
Maintains a strong enthusiasm for staying current with AI research and systems, applying innovative techniques thoughtfully in production.

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22d ago

Lead Machine Learning Engineer (Manager IC)

Capital One McLean, VA

McLean, VA

22d ago

Full time Manager Ai Ml Artificial Intelligence

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Job Description

Role context: This onsite Lead Machine Learning Engineer (Manager IC) role at Capital One centers on designing, deploying, and supporting AI powered software and ML systems across Risk Tech. The position collaborates with cross-functional teams to help shape Capital One's long-term AI roadmap.

Role Overview

This position leads the development and operationalization of AI and ML capabilities, ensuring robust, scalable solutions that drive value for associates and customers within Risk Tech. The role combines hands-on engineering with strategic vision to advance Capital One's AI agenda.

Responsibilities

Collaborate with engineers, data scientists, product managers, and designers to deliver AI powered products that improve associates' workflows and create customer value.
Architect, build, test, deploy, and support AI software components that rely on machine learning models, including evaluation, 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 a cross-functional Agile 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 AI systems roadmap at Capital One.
Utilize a broad stack of open source and SaaS AI technologies.
Inform ML infrastructure decisions with a solid understanding of modeling techniques and associated issues.
Retrain, maintain, and monitor models in production.
Design optimized data pipelines to feed ML models.
Ensure code quality and security, maintain model governance from a risk perspective, and follow responsible and explainable AI best practices.

Requirements

Bachelor’s Degree.
Minimum six years of experience designing and building data‑intensive solutions using distributed computing (internship experience not applicable).
At least four years of experience programming with Python, Scala, or Java.
At least two 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

Strategic & Business‑Oriented

Looks beyond technology to understand business needs and how AI can deliver value. Prioritizes work that translates into meaningful business outcomes.

Highly Collaborative & Transparent

Works effectively across engineering, product, and data science teams. Communicates progress, blockers, and decisions clearly, and shares knowledge to support the team’s success.

Technically Mature & Humble

Grounded in engineering and mathematics, capable of clarifying complex problems and articulating findings concisely. Demonstrates professional maturity in aligning with team decisions.

Flexible & Fungible

Willing to contribute across the tech stack and adapt to changing priorities, providing value wherever needed.

A Lifelong Learner

Keeps current with AI research and responsibly applies novel techniques to production systems, with a clear focus on business impact.

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22d ago

Sr. Lead Machine Learning Engineer

Capital One McLean, VA

McLean, VA

22d ago

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

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Job Description

Capital One seeks a Senior Lead Machine Learning Engineer to design, develop, and productionize scalable ML solutions within an Agile team. The role emphasizes ML design, model and application code review, and maintaining high availability and performance. This on-site position is based in McLean, VA with a salary range of USD 229,900 to 262,400 per year.

Role Details

Location: McLean, VA (onsite)
Salary: USD 229,900 - 262,400 per year
Minimum experience: 2 years
Education: Bachelor’s Degree

Responsibilities

Design and deliver ML models and components that address real business needs, collaborating with Product and Data Science teams
Guide ML infrastructure decisions by applying knowledge of modeling techniques, including model choice, data selection, feature engineering, training, hyperparameter tuning, dimensionality, bias versus variance, and validation
Address complex problems by developing and testing application code, building validated ML models, and automating tests and deployment
Work within a cross functional Agile team to create and improve software powering advanced big data and ML applications
Retrain, maintain, and monitor models in production environments
Leverage or construct cloud based architectures and platforms to deliver optimized ML models at scale
Build optimized data pipelines to feed ML models
Adopt continuous integration and continuous deployment practices, including test automation and monitoring, to ensure successful deployment
Maintain well governed codebases to reduce vulnerabilities and ensure responsible and explainable AI practices
Program using languages such as 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 related field
Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
4+ years of practical experience with an industry recognized ML framework like scikit-learn, PyTorch, Dask, Spark, or TensorFlow
3+ years of writing performant, resilient, and maintainable code
3+ years of experience gathering and preparing data for ML models
3+ years of people management experience
Impact in the ML field through conferences, publications, blog posts, open source work, or patents
3+ years building production ready data pipelines that feed ML models
Ability to clearly communicate complex technical concepts to diverse audiences
Experience leveraging 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

Benefits

Health benefits
Financial benefits
Performance-based incentive compensation, including cash bonuses and long term incentives

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22d ago

Senior Lead Machine Learning Engineer (Intelligent Foundations and Experiences)

Capital One New York, NY

New York, NY

22d ago

$251k - $286k/yr Full time Senior AI Enablement Ai Ml

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Job Description

Capital One is hiring a Senior Lead Machine Learning Engineer in New York, NY onsite to productionize ML applications, lead cross-functional teams, and build scalable AI-driven products, with a salary range of USD 250,800 - 286,200 per year.

Responsibilities

Lead cross functional pods of software, data, and ML engineers to develop AI and ML capabilities for Credit and Financial Risk Management products, acting as a technical mentor on core technologies
Design and deliver AI powered products and components that address real business needs, applying model experimentation, LLM inference, similarity search, and agentic AI within a collaborative Product and Data Science setting
Partner with engineers, data scientists, and designers to develop scalable AI powered products that improve associate performance and deliver standout customer value
Guide ML infrastructure choices based on modeling techniques and challenges, including model selection, data and feature considerations, training, hyperparameters, dimensionality, bias/variance, and validation
Develop and validate ML models, write application code, and automate tests and deployment to address complex problems
Retrain, maintain, and monitor deployed models in production
Utilize or build cloud based architectures and platforms to deploy scalable ML models
Create efficient data pipelines to feed ML models
Apply CI/CD best practices, with test automation and monitoring, to ensure reliable deployment of ML models and code
Ensure code is well managed to minimize vulnerabilities, maintain model governance, and follow Responsible and Explainable AI practices
Utilize a broad mix of open source and SaaS AI technologies, with proficiency in Python, Scala, or Java

Requirements

Bachelor’s Degree required
8+ years designing and building data‑intensive solutions on distributed computing platforms; internship experience not eligible
4+ years programming in Python, Scala, or Java
3+ years building, scaling, and optimizing ML systems
2+ years leading teams delivering ML solutions