Role: Your Impact and Ownership

Own and scale end-to-end ML systems across product lifecycle, partnering with product and engineering teams while mentoring ML engineers.

Key Responsibilities at this Role

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Lead end-to-end development and deployment of scalable ML products in production environments.

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Design real-time and batch ML serving architectures with monitoring and feedback mechanisms.

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Optimize transformer-based models for inference performance, scalability, and production reliability.

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Drive architecture decisions across data pipelines, training infrastructure, and ML platforms.

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Mentor junior ML engineers through code reviews, technical guidance, and design reviews.

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Collaborate with product and engineering teams to align ML outcomes with business impact.

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Own ML initiatives from ideation through deployment, scaling, and continuous improvement.

Skill: The Expertise RequiredMust-Haves for this Role

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Build and deploy production-grade Machine Learning and Transformer models, from data preparation and training to model serving, monitoring, and continuous improvement.

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Develop and optimize Large Language Models (LLMs) using Hugging Face, PyTorch, LoRA/QLoRA, embeddings, quantization, and inference optimization techniques.

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Design scalable ML platforms with data pipelines, training pipelines, MLOps, Docker, Kubernetes, Spark, Airflow, Kafka, and MLflow.

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Build high-performance AI applications using Python, FastAPI, REST/gRPC APIs, real-time and batch inference, distributed systems, and model serving frameworks.

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Lead ML system design, architecture, technical strategy, mentoring, and end-to-end delivery of scalable production AI solutions

📌 Principal ML Engineer (Bengaluru)
🏢 CGvak Software Exports
📍 Bengaluru