Full Stack Machine Learning Systems Architect

1 day ago

Varanasi, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Senior Machine Learning Engineer Role

We are looking for a skilled Senior Machine Learning Engineer to join our team.

This is a challenging and rewarding role that requires expertise in designing, implementing, and scaling machine learning systems. The ideal candidate will have a strong background in software engineering, cloud platforms, Kubernetes, Docker, Terraform, Helm, Kubeflow, and MLflow. Additionally, they should have experience with inference frameworks such as Triton, TensorFlow Serving, BentoML, and TorchServe.

The successful candidate will be responsible for building reliable and scalable machine learning systems in production. They will also contribute to the development of vector database integrations, agent orchestration, multi-tenant security, observability stacks, and CI/CD pipelines.

  • Key Responsibilities:
  • Design and implement scalable machine learning pipelines for large-scale models.
  • Lead efforts in model serving, versioning, automated CI/CD, and real-time monitoring of AI workflows.
  • Build and optimize GPU-backed serving infrastructure targeting low latency and high uptime.
  • Drive initiatives on model governance, automated drift detection, and data-management best practices.
  • Integrate vector databases for low-latency semantic retrieval and build agentic workflows using LangChain or similar frameworks.
  • Architect RBAC-driven, isolated ML services to securely serve multiple organizations.

Requirements:

The ideal candidate will have 9–14 years of experience in software engineering, including at least 4 years in MLOps or ML infrastructure. They should have a strong understanding of distributed training, workload schedulers, and GPU-cluster orchestration. Proficiency in Python, TypeScript, and infrastructure-as-code is also required.

Bonus Skills:

A Master's/PhD in CS/AI and certifications such as AWS ML Specialty, Google Cloud Professional ML Engineer, or CNCF CKA/CKAD would be beneficial. Prior experience at AI-focused startups or enterprises scaling ML for multiple organizations is also desirable. Additionally, an understanding of low-latency streaming inference or agent-based LLM systems would be advantageous.

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