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Senior Machine Learning Engineer at Wand AI | JobVerse
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Senior Machine Learning Engineer
Wand AI
Remote
Website
LinkedIn
Senior Machine Learning Engineer
United States
Full Time
2 hours ago
No Visa Sponsorship
Apply Now
Key skills
AWS
Azure
Cloud
Distributed Systems
Google Cloud Platform
Python
AI
Machine Learning
ML
Agentic
MLOps
GCP
Google Cloud
CI/CD
About this role
Role Overview
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.
Implement pipelines for experimentation, productionization, and continuous agentic learning.
Collaborate with data science and product teams to turn research outputs into production AI agents.
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.
Ensure reliability, scalability, and operational excellence of ML services powering autonomous workflows.
Troubleshoot complex issues in ML pipelines, agentic systems, and distributed infrastructure.
Contribute to CI/CD and development workflows supporting ML lifecycle, agent orchestration, and model deployment.
Collaborate and share knowledge to improve implementation of agentic AI systems across teams.
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 and autonomous workflows.
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.
Experience with highly available model serving systems supporting autonomous agentic tasks.
Strong debugging and troubleshooting skills in complex ML and agentic AI production environments.
Ability to work independently and collaboratively within cross-functional teams.
Tech Stack
AWS
Azure
Cloud
Distributed Systems
Google Cloud Platform
Python
Benefits
Health insurance
Professional development opportunities
Apply Now
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