AI Agent Deployment And PyTorch Neural Network Specialist

What role will you play in the team

You will operate at the cutting edge of artificial intelligence, taking ownership of deploying autonomous AI agents and complex neural network architectures into production systems. Your contributions will directly drive our automated cognitive services, bridging the gap between advanced deep learning research and enterprise-grade software execution.

What you will do

You will build, containerize, and orchestrate advanced AI agents using PyTorch and associated LLM frameworks. Your responsibilities include optimizing model inference speeds, managing API integrations with foundational models, and implementing rigorous testing pipelines to evaluate agentic workflow reliability under diverse operational scenarios.

Key responsibility

• Deploy, manage, and scale AI Agent Deployment pipelines and autonomous execution frameworks in production environments.
• Design, train, and fine-tune deep learning models utilizing PyTorch and advanced neural network architectures.
• Integrate Large Language Models and APIs and webhooks into enterprise applications for automated decision-making.
• Optimize inference performance, reduce memory overhead, and implement quantization strategies for deployed models.
• Monitor agent behavior, analyze failure cases, and continuously retrain models to enhance operational accuracy and safety.

Required Qualification and Skills

• Master's or Bachelor's degree in Artificial Intelligence, Computer Science, or Computational Statistics.
• 1 to 2 years of dedicated practical experience in PyTorch development and machine learning deployment.
• Demonstrated expertise in AI Agent Deployment, Prompt Engineering, and Large Language Models integration.
• Proficiency in Python programming, RESTful APIs, and containerization tools like Docker and Kubernetes.
• Familiarity with vector databases and retrieval systems for augmenting model knowledge bases.

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Benefits Included

• Competitive annual compensation package with performance-based bonuses and stock options.
• Comprehensive medical, dental, and vision insurance plans for complete peace of mind.
• Dedicated learning budget for pursuing advanced AI certifications and attending global tech summits.
• Ample paid time off, parental leave, and flexible hybrid work arrangements.
• Access to state-of-the-art GPU computing clusters and collaborative innovation labs.

A Day in the Life

Your morning kicks off with a stand-up meeting discussing the deployment status of a new customer service AI agent. You then spend hours fine-tuning a PyTorch classification model and optimizing its inference latency. In the afternoon, you configure API webhooks to connect the agent with enterprise CRM tools, concluding the day by running automated evaluation benchmarks.