Senior ML Engineering Lead - Remote

Caylent; United States; Remote; USD 180,000 - 280,000; Full time

Benefits offered by this job

100% remote work

Flexible Time Off

Phantom equity

Paid for exams and certifications

Peer bonus awards

State of the art laptop and tools

Equipment & Office Stipend

Individual professional development

Annual Learning and Development Stipid

Global team culture

Job summary

Caylent is seeking a senior ML leader to guide a team of engineers and architects in a fully remote, international setting. You will own hiring, development, and team health while driving complex customer engagements, shaping architecture, and leading pre-sales efforts.

Bring deep AWS ML and GenAI expertise, a track record of client-facing success, and the ability to translate ML tradeoffs into business value for executives. Remote work, global teams, and a strong focus on responsible AI.

Qualifications

• 10+ years in machine learning or AI with client-facing leadership.
• Proven people management, hiring, and career development ability.
• Deep AWS ML/GenAI knowledge; architect ML lifecycle end-to-end.
• Expertise across multiple ML domains and production systems.
• Ability to translate ML tradeoffs into business value for execs.
• Experience shaping practice standards and reusable accelerators.
• Fluency in responsible AI practices and governance.

Responsibilities

• Lead ML engagements end-to-end with architectural direction.
• Manage and grow a team of ML engineers and architects.
• Drive pre-sales and technical scoping with sales teams.
• Mentor staff, set performance standards, and hire talent.

Skills

ML leadership

Client-facing engagements

People management

AWS ML ecosystem

GenAI & MLOps

Architectural governance

Tools

AWS SageMaker

LLM APIs

MLflow

Kubernetes

Bedrock

SageMaker Pipelines

Job description

Caylent is seeking a senior ML leader to guide a team of engineers and architects in a fully remote, international setting. You will own hiring, development, and team health while driving complex customer engagements, shaping architecture, and leading pre-sales efforts.

Bring deep AWS ML and GenAI expertise, a track record of client-facing success, and the ability to translate ML tradeoffs into business value for executives. Remote work, global teams, and a strong focus on responsible AI.