onsite
Machine Learning Engineer - Agentic AI Systems
ML Engineer
Lead the design and deployment of agentic AI models focused on abstractive summarization, leveraging active learning and deep learning techniques while ensuring strict data privacy compliance.
About the role
Key Responsibilities
- Develop and optimize deep learning architectures for abstractive summarization tasks in agentic AI systems.
- Implement active learning pipelines to efficiently label and refine training data, reducing annotation costs.
- Collaborate with data privacy teams to embed privacy-preserving techniques and comply with DPO requirements.
- Conduct rigorous evaluation, benchmarking models against industry standards and internal metrics.
- Deploy scalable ML solutions on cloud platforms, ensuring high availability and performance.
Requirements
- Strong background in machine learning and deep learning, with hands‑on experience in NLP and summarization.
- Proficiency in Python, PyTorch or TensorFlow, and experience with active learning frameworks.
- Deep understanding of data privacy regulations (GDPR, CCPA) and practical implementation of privacy safeguards.
- Excellent problem‑solving skills and ability to translate research into production systems.
- Effective communication skills to collaborate across cross‑functional teams.
Skills
machine learningdeep learning