Senior Machine Learning Engineer
Job Description
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
- 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
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
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