Description

Build and deploy autonomous AI agents and predictive models to solve complex operational challenges.

This role is on-site.

Responsibilities

• Develop machine learning models using Python, PyTorch, and TensorFlow for high predictive accuracy.
• Implement agentic frameworks like LangChain or LangGraph to address autonomous operation needs.
• Manage the MLOps lifecycle on Databricks or SageMaker, ensuring scalable model delivery.
• Optimize LLM deployment strategies, including RAG, fine-tuning, and inference in hybrid cloud environments.
• Translate complex quantitative findings into strategic recommendations for C-suite stakeholders.

Required Skills

• 5+ years of experience in data science with a Bachelor’s degree in a quantitative field.
• 2+ years of hands-on experience with Python, PyTorch, or TensorFlow.
• Proficiency with Databricks, Spark, or AWS (SageMaker/Bedrock).
• Strong command of SQL and cloud-native orchestration tools like dbt or Airflow.
• Deep understanding of AI governance, including NIST AI RMF and responsible AI principles.
• Experience with LLM deployment, RAG optimization, and performance inference.
• Ability to communicate technical concepts to non-technical leadership.

Preferred Skills

• Familiarity with TM Forum ODA or telecom-specific data models.
• Experience with on-premises AI infrastructure, GPU cluster provisioning, or Kubernetes.
• Background in knowledge graphs or enterprise search optimization.

Key Skills

Education

Bachelor's degree