Staff Machine Learning Engineer

Responsibilities

• Architect and lead the development of scalable ML platforms that support autonomous, goal-driven AI agents.
• Design systems supporting the full ML lifecycle, including agentic decision-making, task orchestration, and automated goal execution.
• Build frameworks for integrating models with product logic, business objectives, and operational workflows.
• Lead the development of pipelines for experimentation, productionization, and continuous agentic learning.
• Design infrastructure supporting large-scale training, inference, and multi-agent coordination workloads.
• Strengthen observability and monitoring across pipelines, AI agents, and goal-driven behavior execution.
• Mentor engineers to build expertise in agentic systems, AI-driven product logic, and autonomous workflows.

Requirements

• Extensive hands-on experience building production ML systems integrated with product goals and business logic.
• Deep expertise in agentic AI, ML engineering, and MLOps practices.
• Strong programming skills in Python and experience integrating ML with backend systems.
• Proven experience deploying machine learning models at scale, including goal-driven or multi-agent systems.
• Strong understanding of distributed systems, scalable data pipelines, and real-time agentic decision loops.
• Experience designing ML systems on cloud platforms such as AWS, Azure, or GCP.
• Ability to lead complex technical initiatives and influence architecture across engineering teams.

Preferred Qualifications

• Experience with NLP, LLMs, generative AI, or multi-agent systems.
• Experience building feature stores or shared ML infrastructure supporting agentic reasoning.
• Experience operating ML workloads on Kubernetes-based infrastructure.
• Experience designing systems for real-time goal-driven inference and autonomous execution at scale.
• Experience building ML systems in enterprise SaaS or large-scale product environments.

About the Company

Wand turns AI into labor. We built the world’s first Agentic Labor Infrastructure, enabling governments and global enterprises to create, manage, and scale digital workforces. Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy.