Lead ML & Data Platform Engineer - Scalable AI Infra

Deca Talent; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Deca Talent is seeking a Lead ML & Data Platform Engineer to own the data processing pipelines and ML platform for next-generation World Models. You will design scalable data and ML infrastructure, build pipelines for ingesting and serving vast datasets, and collaborate with ML researchers to accelerate model training and evaluation in cloud and GPU-heavy environments.

Candidates should have strong software engineering fundamentals, experience with ML infrastructure, Python or Go, data

Qualifications

• Strong software engineering fundamentals for production infra.
• Experience with ML infrastructure or large-scale distributed systems.
• Experience with Python and/or Go.
• Experience building data pipelines and working with large datasets.

Responsibilities

• Design and build scalable data and ML infrastructure for large-scale model development.
• Build reliable pipelines for ingesting, processing, transforming, and serving data.
• Develop infrastructure linking datasets, training runs, model versions, experiments, and inference.
• Track data lineage, metadata, and ML artifacts.
• Collaborate with ML researchers to improve training speed and reproducibility.
• Develop distributed systems across cloud, clusters, and GPUs.
• Support architectural decisions as ML infra scales.
• Identify bottlenecks and implement pragmatic solutions.

Skills

Software engineering

ML infrastructure

Data pipelines

Cloud computing

Kubernetes

Distributed systems

Tools

Python

Go

Kubernetes

Cloud platforms

Job description

Deca Talent is seeking a Lead ML & Data Platform Engineer to own the data processing pipelines and ML platform for next-generation World Models. You will design scalable data and ML infrastructure, build pipelines for ingesting and serving vast datasets, and collaborate with ML researchers to accelerate model training and evaluation in cloud and GPU-heavy environments.

Candidates should have strong software engineering fundamentals, experience with ML infrastructure, Python or Go, data