AI/ML Engineering Manager

• Report to the Director of AI/ML
• Hire and build the ML team; set the technical bar, oversee technical assessments, and make hiring decisions
• Develop people through structured 1:1s, candid feedback, and career growth investment
• Manage performance and partner with HRBPs and the Director of AI/ML when needed
• Monitor staffing, utilization, skills evolution, and engagement assignments
• Lead end-to-end ML assessments covering infrastructure, data pipelines, model lifecycle, and organizational readiness
• Produce recommendations that drive executive decisions and future engagements
• Serve as senior technical authority, shape architecture, set technical direction, and ensure technical quality
• Advise customers on sustainable MLOps, LLMOps, and production monitoring standards
• Partner with sales and solutions teams on scoping and proposals
• Lead customer engagements from kickoff through delivery
• Unblock teams on complex technical problems and ensure Caylent quality standards
• Own architect-level client outcomes or provide senior technical oversight
• Mentor engineers and architects, contribute to technical interviews, and build reference architectures and ML accelerators
• May require up to 25% travel depending on business needs

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity
• Demonstrated people management experience — hiring, performance calibration, career development, and the ability to have difficult conversations directly and constructively
• Deep, current knowledge of the AWS ML and GenAI ecosystem
• Ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring
• Deep expertise in at least two or three ML domains, such as classical ML, computer vision, NLP, or time series
• Proven ability to architect and govern production ML systems end-to-end
• Experience with MLOps, LLMOps, and broader AI operations
• Deep expertise in foundation model adaptation: fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization, and distributed training
• Experience with RAG and agentic system design, including multi-agent architectures, MCP integration, and human-in-the-loop patterns on AWS
• Proven ability to operate independently in complex, ambiguous customer environments
• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional (strong differentiators)
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators (strong differentiator)
• Exposure to varied industries and problem types in a consulting or client-facing context (strong differentiator)
• Fluency in responsible AI practices, including model evaluation, bias detection, fairness frameworks, and AI governance (strong differentiator)
• Fluency in AIOps patterns (strong differentiator)
• Current legal authorization to work in Argentina; Caylent is not able to sponsor visa or work permit applications

• Pay in USD
• 100% remote work
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture