Senior ML Platform Engineer — Remote

Block; San Francisco (CA); Remote; USD 229,000 - 343,000; Full time

Benefits offered by this job

Remote work

Medical insurance

Flexible time off

Retirement savings plans

Family planning

Job summary

Block’s Machine Learning Platform team builds shared infrastructure to help teams develop, evaluate, deploy, and monitor models and automated decision systems. You will design, build, and operate ML infrastructure, lead large-scale distributed systems, and mentor engineers across a broad ML lifecycle.

You will collaborate with applied ML teams across Block, shape roadmaps, and help other engineers grow through design reviews.

Qualifications

• 8+ years of experience in software development and/or machine learning with a focus on internal platforms or infrastructure.
• Hands-on experience building and operating ML infrastructure in feature stores, rules engines, model hosting/inference, or training infrastructure.
• Deep understanding of ML lifecycle and architectures for ML-backed solutions, including data gathering, training, evaluation, and productionizing models (classical ML and DL/LLMs).
• Experience designing and operating large-scale distributed systems with attention to failure modes, data correctness, and performance/capacity.
• Experience operating mission-critical services with oncall and incident response improvements.
• Experience leading complex technical work from conception to delivery with cross-team collaboration.
• Experience mentoring engineers and explaining technical trade-offs to non-experts.
• Experience with major cloud vendors for high-scale production use cases.
• Strong verbal and written communication with technical and non-technical stakeholders.
• Ruthless pragmatism in solving new and unconventional problems.

Responsibilities

• Design, build, and operate shared ML infrastructure (feature stores, rules engines, model hosting/inference, training infra).
• Lead design and delivery of large-scale distributed systems balancing latency, throughput, data consistency, availability and cost.
• Collaborate with ML teams to understand challenges and translate them into reusable platform capabilities; influence roadmap.
• Build reliable services through automated testing, monitoring, capacity planning, and safe deployments.
• Participate in on-call rotation, lead incident response and root-cause analysis to prevent recurrence.
• Create self-service interfaces, libraries, tools, and docs to help teams productionize models and monitor performance.
• Mentor engineers, guide design reviews, and share practices for reliable systems.
• Engage with teams using the platform, explaining design choices and trade-offs.

Skills

Distributed systems design

Oncall & incident response

Mentoring engineers

Stakeholder communication

Cloud vendor communication

Tools

Kotlin / Java

Golang

Python

Typescript

React

gRPC

Protocol Buffers

AWS (Sagemaker, EC2, EKS, Dynamo)

Databricks (Spark)

NVidia Triton

vLLM

ONNX

Job description

Block’s Machine Learning Platform team builds shared infrastructure to help teams develop, evaluate, deploy, and monitor models and automated decision systems. You will design, build, and operate ML infrastructure, lead large-scale distributed systems, and mentor engineers across a broad ML lifecycle.

You will collaborate with applied ML teams across Block, shape roadmaps, and help other engineers grow through design reviews.