Overview
The AI/ML Engineer will play a pivotal role in developing and implementing real-world AI and machine learning systems while collaborating with various teams. They will leverage their extensive experience in software engineering and applied machine learning to build generative AI applications, focusing on agent design, orchestration, and advanced planning strategies. This hybrid role allows the engineer to work both remotely and on-site while engaging with innovative technologies in a dynamic environment.
Responsibilities
- Develop and implement AI/ML systems using Python and backend frameworks.
- Build and integrate GenAI applications with LangChain and LangGraph.
- Design and orchestrate AI agents, managing state and memory effectively.
- Collaborate across teams to ensure scalable, production-ready AI solutions.
- Utilize cloud platforms and manage MLOps processes for AI deployments.
- Evaluate and fine-tune models using technologies such as OpenAI and LLaMA.
- Monitor agent performance using observability tools like LangSmith and LangFuse.
- Provide expertise in software engineering and secure development practices.
Requirements
- 7+ years of experience in software engineering or applied machine learning.
- Strong proficiency in Python and backend development using FastAPI.
- Hands-on experience with GenAI applications, including embeddings and vector stores.
- Familiarity with ML/NLP techniques and generative models.
- Experience with frameworks such as PyTorch, TensorFlow, and MLflow.
- Knowledge of cloud platforms, especially AWS, and MLOps practices.
- Understanding of agent frameworks and agent observability tools.
- Experience working in enterprise environments with secure deployment practices.