AI/ML Engineering Manager

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an AI/ML Engineering Manager in Brazil.

In this role, you will lead a high-performing machine learning engineering team while also acting as a senior technical authority on complex AI and GenAI client engagements. You will operate at the intersection of people leadership, architecture design, and hands-on delivery, ensuring both team growth and technical excellence. Your work will directly influence how enterprise clients design, deploy, and scale production-ready ML systems on AWS. You will guide critical decisions across ML architecture, MLOps, and GenAI solutions while shaping best practices across the practice. This is a highly strategic and client-facing role where you will also contribute to pre-sales, solution design, and technical advisory. It’s an ideal opportunity for a leader who thrives in ambiguity, enjoys deep technical challenges, and is passionate about building impactful AI systems and strong engineering teams.

• Lead, grow, and develop a team of ML engineers and architects, including hiring, performance management, and career development
• Define technical standards and ensure high-quality delivery across machine learning engagements
• Act as senior technical authority on client projects, guiding architecture decisions and solution design
• Lead end-to-end ML assessments, identifying opportunities and risks across data, infrastructure, and model lifecycle
• Drive pre-sales and solutioning efforts in collaboration with sales and delivery teams
• Oversee delivery of ML solutions from design to production, ensuring scalability, reliability, and maintainability
• Advise clients on MLOps, LLMOps, and production AI system design and operations
• Mentor engineers and contribute to building internal accelerators and reference architectures
• Ensure effective staffing alignment and support team utilization across engagements
• Support technical excellence through code reviews, architecture governance, and best practice adoption

Requirements:

• 10+ years of experience in machine learning or AI, including client-facing or consulting roles
• Proven experience in people management, including hiring, coaching, and performance management
• Deep expertise in AWS ML and GenAI ecosystem (e.g., SageMaker, Bedrock, ML pipelines)
• Strong experience designing and governing production-grade ML systems end-to-end
• Expertise across multiple ML domains (e.g., NLP, CV, classical ML, generative AI)
• Strong knowledge of MLOps/LLMOps, including deployment, monitoring, and lifecycle management
• Experience with foundation models, including fine-tuning, RAG, and agent-based architectures
• Ability to translate complex technical decisions into business value for executive stakeholders
• Experience working in ambiguous, fast-paced, client-driven environments
• Strong communication, leadership, and stakeholder management skills

Nice to have:

• AWS certifications (Machine Learning – Specialty, Solutions Architect – Professional)
• Experience building reusable ML frameworks, accelerators, or reference architectures
• Knowledge of responsible AI, governance, bias detection, and fairness frameworks
• Exposure to AIOps and AI-driven automation for observability and operations

Benefits:

• 100% remote work environment
• Flexible time off policy
• Competitive phantom equity program
• Paid certifications and exam reimbursements
• Annual learning and development budget
• Equipment and office stipend for home setup
• High-quality laptop and work tools provided
• Peer recognition and bonus programs
• Individualized professional development planning
• Opportunity to work with a global, highly skilled AI/ML team
• Up to 25% travel depending on project needs