Senior ML Platform Engineer — Scalable AI Infra (Hybrid)

Socket.dev; San Francisco (CA); Hybrid; USD 187,000 - 259,000; Full time

Benefits offered by this job

Four days in office

Fridays from home

Comprehensive health benefits

Wellness stipend

Paid parental leave

Job summary

Chime’s Machine Learning Platform (MLP) team builds the infrastructure, tooling, and developer experience for ML across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently.

As a Senior Software Engineer on the MLP team, you will design and build scalable systems spanning traditional ML and AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic

Qualifications

• 5+ years of experience in ML or AI infrastructure, platform engineering, distributed systems, or production ML systems.
• Experience designing distributed systems and large-scale data or compute platforms on AWS using frameworks such as Spark or Ray.
• Hands-on experience with CI/CD pipelines, DevOps practices, and infrastructure as code.

Responsibilities

• Design, build, and operate scalable ML and AI infrastructure on AWS.
• Design and operate shared platform capabilities for LLM and agentic workloads, including model access, prompt and configuration lifecycle, retrieval, tool integration, state management, and workflow orchestration.
• Build evaluation frameworks for non-deterministic AI systems, including offline benchmarks, regression testing, online quality signals, human feedback, and failure analysis.
• Establish observability, reliability, and governance for models and agents, covering traces, model and prompt versions, tool calls, latency, token usage, quality, safety, privacy, and cost.
• Help teams make principled architecture decisions across traditional ML, LLM-powered applications, and agentic workflows, and contribute to the platform’s technical roadmap.
• Build distributed training, batch inference, and large-scale processing systems using frameworks such as Ray or Spark.
• Build and maintain infrastructure as code using Terraform.
• Support and evolve the feature store and feature pipelines.
• Develop data ingestion and streaming systems using technologies such as Kinesis, Kafka, Flink, or Spark.
• Improve CI/CD workflows for ML models, AI applications, and platform components.
• Partner closely with Data Science and ML Engineering teams to improve developer experience.
• Participate in on-call rotations to support production systems.

Skills

Python

Go

Scala

Java

CI/CD

Distributed systems

AWS

LLM / agentic patterns

Observability

Software testing

Tools

Docker

Kubernetes

Terraform

Ray

Spark

Flink

Kafka

Kinesis

Git

Job description

Chime’s Machine Learning Platform (MLP) team builds the infrastructure, tooling, and developer experience for ML across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently.

As a Senior Software Engineer on the MLP team, you will design and build scalable systems spanning traditional ML and AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic