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docker aws kubernetes pytorch mlops📋 Description
- Lead end-to-end ML assessments across infra, data, and model lifecycle.
- Partner with sales and solutions to shape the SOW.
- Serve as senior technical authority on client engagements.
- Own or orchestrate high-quality POCs for customer confidence.
- Advise on ML ops standards and architecture (MLOps, LLMOps, monitoring).
- Shape Caylent's approach for technically complex opportunities.
🎯 Requirements
- 10+ years in ML/AI with client-facing leadership.
- Deep AWS ML and GenAI knowledge across the full ML lifecycle.
- Expertise in 2-3 ML domains; advise across the landscape.
- Architect and govern production ML end-to-end; MLOps governance.
- Foundation model adaptation — fine-tuning, RLHF, inference optimization; RAG/multi-agent on AWS.
- Operate independently in complex customer environments; translate ML tradeoffs to business value.
🎁 Benefits
- 100% remote work
- Medical Insurance for you and eligible dependents
- 401k with company match up to 4% and immediate vesting
- Competitive phantom equity
- Company issued laptop
- Unlimited Paid Time Off, with 10 paid holidays
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