AI/ML Engineering Manager

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Recruit and establish the ML team, define technical standards, supervise technical evaluations, and make recruitment choices.

• Facilitate structured one-on-one meetings, offer constructive feedback, and assist team members in their career progression.

• Manage team performance, collaborate with HRBPs and the Director of AI/ML, and advocate for team interests.

• Oversee staffing and ensure that team members are appropriately allocated across various projects.

• Lead comprehensive ML assessments of client environments and deliver executive-level recommendations.

• Design engagement architecture and act as a senior technical authority.

• Provide guidance to clients on MLOps, LLMOps, production monitoring, and sustainable ML systems.

• Collaborate with sales and solutions teams on project scoping and proposal development.

• Direct architecture and solution design from project initiation to delivery.

• Take ownership of architect-level client outcomes or offer senior technical oversight.

• Mentor engineers and architects, participate in technical interviews, and develop reference architectures and reusable ML accelerators.

⛳️ Requirements

• 10+ years of experience in machine learning or AI, with a solid history of leading client-facing projects in a consulting or advisory role.

• Proven experience in people management, including hiring, performance assessment, career development, and the capacity to engage in challenging conversations directly and effectively.

• Extensive, up-to-date knowledge of the AWS ML and GenAI ecosystem, with the capability to make and justify architectural decisions throughout the entire ML lifecycle—from data and feature engineering to training, deployment, and monitoring.

• In-depth expertise in at least two or three ML domains—such as classical ML, computer vision, NLP, time series, or others—along with the discernment to evaluate, architect, and provide advice across the wider ML landscape.

• Demonstrated ability to design and manage production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexities into standards that engineering teams can implement and executives can act upon.

• Profound knowledge in foundation model adaptation—fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization, and distributed training—combined with RAG and agentic system design, including multi-agent architectures, MCP integration, and human-in-the-loop methodologies on AWS.

• Established aptitude for working independently in intricate, uncertain customer environments—managing conflicting priorities, aligning stakeholders, and converting ML trade-offs into business risks and value for both technical and executive audiences.

• Current legal authorization to work in Brazil; Caylent is unable to sponsor visa or work permit applications.

• Travel of up to 25% may be required based on business needs.

🏝️ Benefits

• 100% remote work

• Flexible Time Off

• Competitive phantom equity

• Coverage 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

• Opportunity to work with an outstanding global team and experience a remarkable corporate culture