Lead Computer Vision Engineer

We are seeking an experienced Lead Computer Vision Engineer to lead the design, development, and deployment of cutting-edge AI and machine learning solutions. The ideal candidate will have strong hands-on expertise in Python, machine learning, and deep learning, along with experience in building scalable production-ready AI systems. This role requires a blend of technical excellence, innovation, leadership, and mentorship, ensuring high-impact delivery aligned to business needs. You will drive experimentation, improve model development pipelines, optimize data workflows, and build reusable AI components. The role involves identifying risks early, ensuring high-quality execution, and contributing to AI capability building across the organization.

The core responsibilities for the job include the following:

Computer Vision Development:

• Architect, develop, and deploy scalable AI/ML models for production with high performance and reliability.
• Build at least two innovative AI solutions aligned with business priorities annually.
• Ensure production-grade AI system delivery with < 5 bugs and strong reliability metrics.
• Improve end-to-end model development pipeline efficiency by at least 20%.
• Develop reusable machine learning modules, tools, and automation frameworks to reduce development complexity.

Data Engineering & Pipeline Optimization:

• Improve data preparation and annotation pipeline efficiency by 50%.
• Collaborate with data engineering teams to design efficient data pipelines and automated preprocessing workflows.
• Work with large datasets, perform data wrangling, feature engineering, and optimize training/validation pipelines.

Innovation & Solution Design:

• Lead research initiatives to design AI-first solutions for new business use cases.
• Evaluate new ML frameworks, model architectures, and tools to continuously enhance system performance.
• Conduct PoCs, benchmark results, and transition validated solutions into scalable production systems.

Quality & Risk Management:

• Identify potential project risks early and mitigate them, reducing unforeseen delivery issues by 99%.
• Enforce best practices in model evaluation, versioning, MLOps, and monitoring for long-term stability.
• Ensure model security, fairness, and compliance standards.

Team Leadership & Mentorship:

• Mentor and guide at least 2+ junior AI engineers to build skill depth and readiness for advanced roles.
• Provide technical leadership on architecture design, experimentation strategy, and performance tuning.
• Help the team resolve primary business dependencies and technical blockers efficiently.

Collaboration:

• Work closely with product, engineering, data, and business teams to convert business needs into AI-driven solutions.
• Communicate progress, risks, and results with stakeholders clearly and effectively.

Requirements:

• Bachelor's/Master's degree in Computer Science, AI/ML, Data Science, or a related field.
• 5+ years of hands-on experience in machine learning and deep learning.
• Strong proficiency in Python and ML libraries (TensorFlow/PyTorch, Scikit-Learn, OpenCV, Hugging Face, etc. ).
• Proven experience deploying AI solutions into production environments (cloud or on-premises).
• Strong understanding of MLOps, CI/CD for ML, containerization (Docker), and orchestration (Kubernetes preferred).
• Experience working with structured & unstructured data (images, video, sensor data, and text).
• Hands-on experience with data pipelines, ETL processes, and real-time inference systems.
• Strong analytical and debugging skills with a track record of shipping stable solutions.
• Understanding of distributed computing frameworks (Spark or similar) is an advantage.