The Senior Advanced Software Engineer will develop end-to-end machine learning pipelines, focusing on computer vision, deep learning, and Generative AI. Responsibilities include deployment, optimization, and mentoring junior staff.
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.
Responsibilities- 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
Top Skills
AWS
Azure
C++
Computer Vision
Deep Learning
Docker
GCP
Generative Ai
Hugging Face
Java
Kubernetes
Python
PyTorch
TensorFlow
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