Software Engineer Machine Learning Engineer Agentic AI

You will design and implement autonomous agent systems that explore, execute, evaluate, and improve engineering solutions. You will develop multi-agent workflows, automated evaluation systems, post-training experiments, and production-quality integrations for engineering workflows.

Responsibilities

• Research and implement agent planning, tool use, memory, reasoning, and self-improvement mechanisms
• Develop multi-agent workflows and orchestration
• Build systems that execute, validate, evaluate, and iteratively improve agent outputs
• Evaluate and optimize agents using LLM-as-a-judge, task-specific metrics, and benchmarks
• Experiment with and apply SFT and reinforcement learning post-training techniques
• Apply Agentic AI and post-training research to engineering problems

Requirements

• Bachelor's degree in Computer Science or a related field
• Model training or experimentation using PyTorch, JAX, TensorFlow, or another ML framework
• Experience implementing or experimenting with LLM or Agentic AI systems
• Ability to understand research papers and turn research into implementations
• Agent system development
• Tool use
• Reasoning
• Memory
• Planning
• Multi-agent orchestration
• SFT
• Reinforcement learning
• Preference optimization
• Agent evaluation
• Benchmark design
• LLM-as-a-judge
• Automated evaluation
• LangGraph
• AutoGen
• Google ADK
• Distributed training
• Inference optimization
• Large-scale experimentation