Senior ML Engineer — Own End-to-End ML Products (Remote)

Talent Inc.; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Careerminds is seeking Machine Learning Engineers to own products end to end—from problem framing to production deployment and measurable impact. You’ll operate in an AI-native environment with Claude Code and Claude Design as default tools, owning experiments and decisions with a founder-like accountability.

The role emphasizes building scalable data pipelines, retrieval and ranking systems, and agentic ML applications while navigating production constraints and governance.

Qualifications

• 5+ years shipping ML systems into production.
• Depth in classical ML and deep learning applied to live products.
• Working fluency with LLMs in production— retrieval, evals, prompt engineering.
• Experience with agentic coding tools— Claude Code / Claude Design.
• Strong software engineering fundamentals: Python, Git, cloud (AWS), containers, and data handling.

Responsibilities

• Own data/identity pipelines from discovery to production and monitoring.
• Lead retrieval, ranking, and matching components for job platforms.
• Develop and evaluate LLM-driven agents with human approvals and governance.
• Build and maintain end-to-end ML systems with telemetry, metrics, and rollbacks.
• Ensure compliance with data privacy and deployment constraints across environments.

Skills

ML systems production

Classical ML & DL

LLMs in production

Agentic coding tools

Python

Git

AWS

Containers

Tools

Claude Code

Claude Design

PyTorch

TensorFlow

AWS

Job description

Careerminds is seeking Machine Learning Engineers to own products end to end—from problem framing to production deployment and measurable impact. You’ll operate in an AI-native environment with Claude Code and Claude Design as default tools, owning experiments and decisions with a founder-like accountability.

The role emphasizes building scalable data pipelines, retrieval and ranking systems, and agentic ML applications while navigating production constraints and governance.