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Sr Staff ML Engineer - Production & MLOps Focus - GenAI Security Platform

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Palo Alto Networks

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Location:
India , Bengaluru

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

Join our team building a cutting-edge multi-tenanted GenAI Security Platform that helps organisations validate and secure their AI systems against adversarial attacks. We're looking for a production-focused ML engineer who can both build ML systems and own their deployment at scale.

Job Responsibility:

  • Build and deploy LLM-based agents and multi-step evaluation workflows
  • Fine-tune models, optimize embeddings, and manage model weights and artifacts
  • Deploy and scale ML services on Kubernetes with proper monitoring and resource management
  • Implement experiment tracking, model versioning, and deployment automation
  • Develop observability dashboards for ML metrics, costs, latency, and quality
  • Optimize LLM API usage through caching, batching, and intelligent routing strategies
  • Manage vector database infrastructure and semantic search systems
  • Create CI/CD pipelines for ML artifacts and automated testing frameworks
  • Collaborate with ML researchers to productionize prototypes and scale experiments

Requirements:

  • 4+ years of ML engineering experience with hands-on LLM/NLP work
  • Practical experience building LLM-based applications (agents, multi-turn systems, evaluators)
  • Understanding of model fine-tuning, embedding optimization, and prompt engineering
  • Experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI)
  • Knowledge of LLM orchestration frameworks ( LangChain, LlamaIndex, Pydantic AI, custom solutions)
  • Familiarity with model architectures and when to fine-tune vs prompt engineer
  • Strong experience deploying ML models to production at scale
  • Experience with Model serving frameworks (vLLM preferred
  • TensorRT-LLM, Ray Serve, or similar a plus)
  • Kubernetes and Docker proficiency for ML workload orchestration
  • Hands-on experience with ML experiment tracking and model versioning tools
  • Understanding of CI/CD for ML systems with automated testing and validation
  • Knowledge of distributed computing, async processing, and job queues
  • Experience with monitoring, observability, and cost optimisation for ML systems
  • Proficiency with cloud platforms (GCP preferred, AWS/Azure acceptable)
  • Experience managing vector databases and similarity search at scale
  • Understanding of caching strategies (Redis) and data pipeline architectures
  • Knowledge of infrastructure-as-code and GitOps workflows
  • Expert Python skills (async/await, type hints, Pydantic, testing)
  • Experience with ML frameworks (PyTorch/TensorFlow helpful but not required)
  • SQL proficiency for analytics and data pipeline development
  • Strong software engineering practices (testing, code review, documentation)

Nice to have:

  • Experience with model training, LoRA, PEFT, or custom fine-tuning pipelines
  • Background in building multi-agent systems or complex LLM workflows
  • Knowledge of AI safety, adversarial ML, or security testing
  • Previous work optimizing LLM costs and latency at scale
  • Familiarity with graph databases or relationship modeling
  • Experience in high-scale production ML environments

Additional Information:

Job Posted:
March 04, 2026

Employment Type:
Fulltime
Work Type:
On-site work
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