Senior Distinguished Engineer, AI Compute (Remote Eligible)
AI summary of the role
This is a hands-on Senior Distinguished Engineer role on Capital One's machine learning platform team, responsible for architecting and scaling the foundational compute infrastructure (CPU/GPU) for AI/ML workloads.
What you’ll do
- Architect and build control and data plane implementations for a highly available, multi-tenant, large scale machine learning platform
- Develop Ray and Spark distributed compute engine solutions to accelerate LLM pre-training, reinforcement learning, and large-scale data processing
- Engineer systemic improvements for operational excellence including automating KTLO workflows
- Direct technical execution of a diverse project portfolio, collaborating with developers on distributed microservices and large foundation models
What you’ll bring
- Bachelor’s Degree
- At least 7 years of experience with application architecture and design patterns
- At least 5 years of experience with distributed databases, microservice architectures, and high availability systems
- Hands-on experience with Golang and Python, distributed compute frameworks (Spark/Dask/Ray/Flink), and container/serverless runtimes (Kubernetes/AWS Lambda)
Technologies
Golang · Python · Spark · Dask · Ray · Flink · Kubernetes · AWS Lambda · EKS · EC2 UltraClusters · Graviton
Source and classification
Internal deployment & tooling · Evidence for this classification:
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. Team Description: The Capital One machine learning platform organization manages our cloud-based enterprise AI+ML system delivering the high-scale developer and runtime environments required to build, orchestrate, and deploy compute and data intensive AI systems across real-time and batch workloads. We are seeking a Senior Distinguished Engineer, a hands-on technical leader passionate about distributed systems, to engineer and scale foundational compute capabilities for our platform. You will use your experience in building large scale, highly available and high performance systems to develop our common compute infrastructure on top of CPU and GPU substrates. Your contributions will power everything from
More from the job description
Senior Distinguished Engineer, AI Compute (Remote Eligible) Overview: 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. Team Description: The Capital One machine learning platform organization manages our cloud-based enterprise AI+ML system delivering the high-scale developer and runtime environments required to build, orchestrate, and deploy compute and data intensive AI systems across real-time and batch workloads. We are seeking a [... source excerpt omitted ...] erverless (e.g., AWS Lambda) runtime environments, and ML+AI workload patterns will provide an amplifying technical element that is paramount to our team's success. In this role, you will : Architect and build control and data plane implementations required to realize a highly available, multi-tenant, large scale and a secure machine learning platform Develop Ray and Spark distributed compute engine solutions to accelerate diverse workloads from LLM pre-training and reinforcement learning to large-scale data processing, while maximizing compute unit economics Engineer systemic improvements for operational excellence including automating KTLO (Keep The Lights On) workflows Di [... source excerpt omitted ...] capabilities Lead the way in creating next-generation talent, mentoring internal talent and actively recruiting external talent to bolster the Capital One tech talent pool Basic Qualifications Bachelor’s Degree At least 7 years of experience with application architecture and design patterns. At least 5 years of experience with distributed databases, microservice architectures, and high availability systems Preferred Qualifications Degree in Computer Science or a Master’s Degree in Software Engineering Hands on experience in the internals of Ray (Actors/GCS/Scheduling) or Spark (Query Optimizer/Memory Management) Experience building platforms that support LLM training, fine-tun
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