Senior Machine Learning Engineer

Responsibilities

• Develop and maintain ML platforms and pipelines supporting autonomous, goal-driven AI agents
• Build systems for the full ML lifecycle, including agentic decision-making, task orchestration, and goal execution
• Integrate ML models with product logic and business workflows to operationalize AI capabilities
• Design and optimize infrastructure for large-scale training, inference, and multi-agent coordination
• Implement observability and monitoring for ML pipelines, agent behaviors, and goal-driven execution
• Build systems for automated evaluation, drift detection, and retraining of AI models
• Collaborate with data science and product teams to turn research outputs into production AI agents

Requirements

• Hands-on experience building production ML systems integrated with product goals and business logic
• Expertise in ML engineering, agentic workflows, and MLOps practices
• Strong programming skills in Python and experience integrating ML with backend systems
• Experience deploying machine learning models at scale, including goal-driven or multi-agent systems
• Experience building ML infrastructure supporting training, experimentation, inference, and agent coordination
• Solid 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

Preferred Qualifications

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

About the Company

Wand turns AI into labor. We have 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.