CrawlJobs Logo
Capital One Logo Capital One · IT - Software Development

Senior Lead Machine Learning Engineer

United States, New York 229900.00 - 286200.00 USD / Year · Job Posted January 31, 2026
Apply Position
Job Link Share

Job Description

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Job Responsibility

  • Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with a cross-functional team of engineers, research scientists, technical program managers, and product managers
  • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more
  • Construct optimized data pipelines to feed ML models
  • Design, develop, test, deploy, and support AI software components including large language model inference, similarity search, model evaluation, experimentation, governance, and observability, etc
  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems
  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One
  • 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 8 years of experience designing and building data-intensive solutions using distributed computing
  • 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

Nice to have

  • Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
  • Experience developing, delivering, and supporting 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 with data gathering and preparation for ML models
  • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents
  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory)
  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
  • Ability to communicate complex technical concepts clearly to a variety of audiences

What we offer

  • comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
  • performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
Capital One - All Job Offers

Looking for more opportunities?

Search for other job offers that match your skills and interests.

Suggested Tags: Frontend Developer Secretary Talent Manager Salesforce Administrator Data Analyst
Similar Jobs for

Senior Lead Machine Learning Engineer

8 matching positions

Senior Lead Machine Learning Engineer

As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile tea...
Location
Location
United States , New York; San Francisco; San Jose; Cambridge; McLean
Salary
Salary:
229900.00 - 286200.00 USD / Year
capitalone.com Logo
Capital One
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s Degree
  • At least 8 years of experience designing and building data-intensive solutions using distributed computing
  • 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
Job Responsibility
Job Responsibility
  • Design, build, and/or deliver ML models and components that solve real-world business problems
  • Inform ML infrastructure decisions using understanding of ML modeling techniques
  • 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
  • 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
  • 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
What we offer
What we offer
  • Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
  • Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
  • Fulltime
Read More
Arrow Right

Senior Lead Machine Learning Engineer

This role combines hands-on machine learning engineering with technical leadersh...
Location
Location
Australia , Brisbane
Salary
Salary:
150000.00 - 190000.00 AUD / Year
reqiva.com Logo
Reqiva
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Degree in Computer Science, Engineering, Data Science, or equivalent experience
  • Strong experience developing production machine learning systems
  • Hands-on expertise with deep learning frameworks such as PyTorch
  • Experience developing computer vision models
Job Responsibility
Job Responsibility
  • Design, train, and evaluate computer vision models including object detection, classification, and segmentation
  • Conduct structured experimentation and performance analysis to guide model architecture decisions
  • Optimise models for edge deployment across embedded hardware platforms
  • Convert and deploy models using frameworks such as TensorRT, ONNX, or TFLite
  • Support development of data pipelines, dataset curation, and annotation workflows
  • Benchmark and tune model performance for latency, accuracy, and operational constraints
  • Contribute to ML assurance practices including validation, benchmarking, and regression testing
  • Mentor engineers and contribute to the growth of the ML capability
  • Fulltime
Read More
Arrow Right

Senior / Lead Machine Learning Engineer, Serving

Inworld is a product-oriented research lab of top AI researchers and engineers, ...
Location
Location
Germany
Salary
Salary:
Not provided
inworld.ai Logo
Inworld AI
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Inference Optimization. Deep understanding of modern serving frameworks and techniques like vLLM or TRT-LLM
  • Model Acceleration. Hands-on experience with quantization, distillation, caching strategies, continuous batching, paged attention, and speculative decoding
  • High-Performance Systems. Proficiency in C++, CUDA, Rust, or highly optimized Python. You know how to profile code and squeeze every ounce of performance out of NVIDIA GPUs
  • Distributed Systems & Scaling. Experience with Kubernetes, Ray, custom load balancing, multi-GPU/multi-node inference, and reliably handling thousands of concurrent connections
  • Public work. Non-trivial systems programming projects, open-source contributions to major inference engines, or deep-dive technical write-ups
  • Full-cycle ownership. You can take a model from the research team, containerize it, optimize its serving, and ensure it runs reliably in production
  • Background. PhD in CS, Physics, Math, or equivalent practical experience building backend or ML systems
  • Professional fluency in English (written and spoken) is required, as you will be collaborating daily with our US-based leadership and engineering teams
Read More
Arrow Right

Senior / Lead Machine Learning Engineer, Serving

Location
Location
Serbia
Salary
Salary:
Not provided
inworld.ai Logo
Inworld AI
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Inference Optimization
  • Model Acceleration
  • High-Performance Systems
  • Distributed Systems & Scaling
  • Public work
  • Full-cycle ownership
  • Background
  • Professional fluency in English
Read More
Arrow Right

Senior Machine Learning Engineer (Team Lead)

As our Artificial Intelligence (AI) and Machine Learning (ML) Team Leader, you w...
Location
Location
Australia , South Bank
Salary
Salary:
Not provided
fctgcareers.com Logo
Flight Centre Brand
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 7+ years delivering production grade ML or AI systems with proven commercial impact
  • 3+ years Leading and Mentoring engineers
  • Experience building AI agents, RAG systems or LLM powered applications in production
  • Demonstrated experience leading technical teams and managing complex AI programmes
  • Strong hands on experience across ML infrastructure, distributed systems and scalable AI architecture
  • Experience building and governing AI agent platforms including endpoints, gateways and tool orchestration
  • Familiarity with MCP servers and emerging agent communication standards and protocols
  • Experience defining evaluation frameworks, safety mechanisms and governance for LLM and agent based systems
  • Deep knowledge of Python, modern AI/ML frameworks and scalable AI platforms including Databricks
  • Strong expertise in Kubernetes and cloud native production environments
Job Responsibility
Job Responsibility
  • Lead the development and productionisation of ML models, LLM powered systems and agent based applications
  • Define and build end to end MLOps including CI CD, model registry, monitoring, drift detection and retraining for predictive ML systems
  • Establish LLMOps standards including context engineering, automated evaluation pipelines, red teaming, safeguards and policy guardrails
  • Architect and build AI agent workflows, endpoints, gateways and orchestration layers enabling secure tool access, structured reasoning and multi agent collaboration
  • Design and govern MCP servers and modern agent communication protocols to ensure interoperability, security and scalability
  • Implement strong observability across ML and GenAI systems including reliability, latency, evaluation metrics, usage tracking and cost control
  • Drive scalable ML infrastructure, feature stores and data platforms on Databricks
  • Oversee Kubernetes based deployments and cloud native AI infrastructure
  • Partner with senior stakeholders to prioritise and deliver multiple high impact AI initiatives
  • Coach and grow a high performing AI engineering team
What we offer
What we offer
  • Individualised, ongoing Learning & Development via communities of practice
  • Innovation Days
  • Dedicated Engineering Days
  • Access to 'LinkedIn Learning' for ongoing skills development
  • Women in PM&E group
  • Exclusive Staff Discounts
  • Travel Discounts
  • Career opportunities in a network of brands and businesses across the globe
  • Corporate Health Discounts
  • Mental Health Support and Employee Assistance Program for staff and family
  • Fulltime
Read More
Arrow Right

Senior Machine Learning Engineer, AI Platform

The AI Platform team is responsible for building the foundational infrastructure...
Location
Location
United States; Canada
Salary
Salary:
139000.00 - 218000.00 USD / Year
mozilla.org Logo
Mozilla
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
  • Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
  • Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
  • Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
  • Hands-on experience working with GPU-based workloads and accelerated computing in production settings
  • Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
  • Ability to independently scope and drive technical initiatives while balancing product and operational priorities
  • Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
  • Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams
Job Responsibility
Job Responsibility
  • Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
  • Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
  • Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
  • Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
  • Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
  • Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
  • Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
  • Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
  • Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews
What we offer
What we offer
  • Generous performance-based bonus plans
  • Rich medical, dental, and vision coverage
  • Generous retirement contributions with 100% immediate vesting
  • Quarterly all-company wellness days
  • Country specific holidays plus a day off for your birthday
  • One-time home office stipend
  • Annual professional development budget
  • Quarterly well-being stipend
  • Considerable paid parental leave
  • Employee referral bonus program
  • Fulltime
Read More
Arrow Right

Senior Machine Learning Engineer – AV Labs

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We'...
Location
Location
United States , Sunnyvale
Salary
Salary:
202000.00 - 224000.00 USD / Year
uber.com Logo
Uber
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 4+ years of working experience in the ML/Robotics industry
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields
  • Proficient in Python and Linux environments
  • Familiar with modern AI/ML frameworks (e.g., PyTorch).
Job Responsibility
Job Responsibility
  • Algorithm Development: Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake
  • Systems Architecture Design: Architect scalable ML systems, including management of upstream sensor dependencies
  • Technical Leadership: Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability
  • Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling
  • Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.
What we offer
What we offer
  • Bonus program
  • Equity award & other types of comp
  • 401(k) plan
  • Various benefits
  • Fulltime
Read More
Arrow Right

Senior Machine Learning Engineer, AI Platform

Location
Location
United States; Canada
Salary
Salary:
128000.00 - 171000.00 CAD / Year
mozilla.org Logo
Mozilla
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent
  • Strong experience developing in Python for machine learning systems, backend services, or distributed data processing
  • Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure
  • Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies)
  • Hands-on experience working with GPU-based workloads and accelerated computing in production settings
  • Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment
  • Ability to independently scope and drive technical initiatives while balancing product and operational priorities
  • Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems
  • Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams
Job Responsibility
Job Responsibility
  • Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments
  • Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence
  • Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads
  • Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization
  • Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation
  • Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines
  • Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features
  • Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing
  • Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews
What we offer
What we offer
  • Generous performance-based bonus plans to all eligible employees
  • Rich medical, dental, and vision coverage
  • Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute)
  • Quarterly all-company wellness days where everyone takes a pause together
  • Country specific holidays plus a day off for your birthday
  • One-time home office stipend
  • Annual professional development budget
  • Quarterly well-being stipend
  • Considerable paid parental leave
  • Employee referral bonus program
  • Fulltime
Read More
Arrow Right