C G Vak Softwares & Exports - Principal Machine Learning Engineer - Python

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

• Lead end-to-end development and deployment of scalable ML products in production environments.
• Design real-time and batch ML serving architectures with monitoring and feedback mechanisms.
• Optimize transformer-based models for inference performance, scalability, and production reliability.
• Drive architecture decisions across data pipelines, training infrastructure, and ML platforms.
• Mentor junior ML engineers through code reviews, technical guidance, and design reviews.
• Collaborate with product and engineering teams to align ML outcomes with business impact.
• Own ML initiatives from ideation through deployment, scaling, and continuous improvement.

Skill: The Expertise Required Must-Haves For This Role

• Build and deploy production-grade Machine Learning and Transformer models, from data preparation and training to model serving, monitoring, and continuous improvement.
• Develop and optimize Large Language Models (LLMs) using Hugging Face, PyTorch, LoRA/QLoRA, embeddings, quantization, and inference optimization techniques.
• Design scalable ML platforms with data pipelines, training pipelines, MLOps, Docker, Kubernetes, Spark, Airflow, Kafka, and MLflow.
• Build high-performance AI applications using Python, FastAPI, REST/gRPC APIs, real-time and batch inference, distributed systems, and model serving frameworks.
• Lead ML system design, architecture, technical strategy, mentoring, and end-to-end delivery of scalable production AI solutions.

(ref:hirist.tech)