17 days ago
Pune, IndiaStaff+
Responsibilities
- Architect and deploy RAG pipelines, agentic workflows, and LLM applications for security telemetry and unstructured logs.
- Train, fine-tune, and evaluate ML and deep learning models for pattern matching, anomaly detection, and classification.
- Implement guardrails, evaluation frameworks, and safety alignment techniques for deterministic, safe, and accurate model outputs.
- Build and maintain scalable MLOps pipelines from data preprocessing through production model monitoring.
- Collaborate with Data and Product Engineers to deliver secure, low-latency inference systems.
- Set technical direction and execute AI initiatives in a small team.
Requirements
- 6+ years of professional experience deploying machine learning models into production.
- 1+ year of experience focused on LLMs and generative AI.
- Deep expertise in Python, PyTorch or TensorFlow, and frameworks such as LangChain, LlamaIndex, or Hugging Face.
- Hands-on experience with vector databases including Pinecone, Qdrant, or Milvus and semantic search over complex technical datasets.
- Understanding of API design, Docker, Kubernetes, and cloud ML platforms such as AWS SageMaker, Azure ML, or GCP Vertex AI.
- Cybersecurity domain experience is highly valued.
- Comfort setting technical direction, navigating ambiguity, and executing quickly in a small-team environment.
Benefits
- Hybrid work arrangement in Pune.
- Equal opportunity employment and a commitment to a diverse workplace.
Tech Stack
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