We are seeking a highly skilled Senior Advanced Software Engineer with deep expertise in computer vision, deep learning, and generative AI (GenAI). This role requires end-to-end ownership of machine learning pipelines, from research and prototyping to deployment and scaling in production environments. The ideal candidate will have profound knowledge of full-stack ML deployment and a proven track record of building robust, scalable systems.
Architect and develop end-to-end ML pipelines for computer vision, deep learning, and GenAI use cases.
Design scalable solutions for data ingestion, preprocessing, training, evaluation, and deployment.
Implement and maintain full-stack ML deployment frameworks across cloud and on-prem environments.
Automate CI/CD workflows for ML models to ensure reproducibility and reliability.
Monitor, troubleshoot, and optimize deployed models for performance, accuracy, and efficiency.
Collaborate with cross-functional teams including data scientists, product managers, and DevOps engineers.
Mentor junior engineers and contribute to technical knowledge sharing across the organization.
Drive innovation by integrating emerging AI/ML technologies into production workflows.
Optimize ML systems for large-scale data, distributed training, and high-throughput inference.
Establish best practices for model versioning, monitoring, retraining, and lifecycle management
Strong background in computer vision, deep learning, and GenAI frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
Expertise in end-to-end ML pipeline development (data engineering, model training, deployment, monitoring).
Expertise in deploying ML models to Edge ( x86, arm64 architectures )
Proficiency in cloud platforms (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes).
Solid understanding of MLOps practices (CI/CD, model versioning, monitoring, retraining).
Experience with full-stack ML deployment including APIs, microservices, and scalable inference systems.
Strong programming skills in Python, C++/Java, and modern ML toolchains.
Excellent problem-solving, communication, and leadership skills.
Preferred Qualifications
- Experience with distributed training frameworks (Horovod, DeepSpeed).
- Knowledge of edge deployment for computer vision models.
- Familiarity with data pipelines (Spark, Kafka, Airflow).
- Contributions to open-source ML/AI projects.
- B.Tech/ M.Tech with 8+ years of experience