🛠 Tech Stack

💼 About This Role

You'll lead a high-performing ML engineering team while acting as a senior technical authority on complex AI and GenAI client engagements. You'll operate at the intersection of people leadership, architecture design, and hands-on delivery, directly influencing how enterprise clients design, deploy, and scale production-ready ML systems on AWS. This client-facing role also involves contributing to pre-sales, solution design, and technical advisory.

🎯 What You'll Do

• Lead, grow, and develop a team of ML engineers and architects
• Define technical standards and ensure high-quality delivery across ML engagements
• Act as senior technical authority on client projects, guiding architecture decisions
• Drive pre-sales and solutioning efforts in collaboration with sales and delivery teams

📋 Requirements

• 10+ years of experience in machine learning or AI, including client-facing roles
• Proven experience in people management, including hiring 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

✨ 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

🎁 Benefits & Perks

• 🏠 100% remote work environment
• ⏰ Flexible time off policy
• 💰 Competitive phantom equity program
• 🎓 Paid certifications and exam reimbursements
• 📚 Annual learning and development budget

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min

🚩 Heads Up

• Up to 25% travel may conflict with fully remote expectation
• Very broad requirements spanning multiple ML domains (NLP, CV, classical ML, GenAI)