onsite
Staff Machine Learning Engineer - Agentic Application
ML Engineer
Lead the design and deployment of agentic AI conversational systems, driving end‑to‑end ML pipelines in Python while collaborating closely with cross‑functional teams to deliver intelligent user interfaces.
About the role
Key Responsibilities
- Architect and implement scalable machine learning models for agentic conversational AI, ensuring high performance and reliability.
- Develop end‑to‑end data pipelines, from data ingestion and preprocessing to model training, evaluation, and deployment.
- Collaborate with product, design, and engineering teams to translate business requirements into technical solutions.
- Mentor junior engineers, conduct code reviews, and promote best practices in ML engineering.
- Stay current with advances in NLP, deep learning, and agentic AI, integrating cutting‑edge techniques into production systems.
Requirements
- 10+ years of experience in machine learning engineering, with a strong focus on conversational AI.
- Proficiency in Python, deep learning frameworks (PyTorch/TensorFlow), and large‑scale data processing.
- Hands‑on experience with NLP models, transformer architectures, and agentic AI concepts.
- Excellent communication skills and a proven track record of cross‑functional collaboration.
- Strong problem‑solving abilities and a passion for building user‑centric AI products.
Skills
machine learningpythonnlpdeep learning