Deputy Director -Machine Learning Engineering

Key Skills

Aartificial intelligence, AIOps, AWS, Azure, Google Cloud Platform (GCP), Keras software library, Machine learning techniques, Python Programming, PyTorch, TensorFlow

Job Description

Responsibilities

• Explore and Architect advanced Computer Vision models for applications in the Cloud involving image/video processing, object detection, and recognition.
• Conduct research to stay up to date with the latest advancements in Computer Vision, machine learning, and deep learning techniques, and identify opportunities for integrating into our products and services.
• Enable a cloud-native solution that is reliable, scalable, and secure.
• Successfully articulate architectural ideas and present them to various stakeholders.
• Lead the technical team to ensure compliance with Architectural standards.
• Create and implement Proof of Concept to validate Architecture decisions.
• Ability to work under tight deadlines and respond to dynamic technical challenges.
• Align business and technical leaders across the solution with strong architecture inputs.
• Active participation in architecture/design reviews, code reviews.
• Provide Technical leadership and mentorship to Staff.
• Develop and maintain documentation for the design and solution involving Cloud-native AI technologies.

Qualifications

Years of Experience

• 3+ years’ experience in architecting and implementing computer vision and image processing models and frameworks in large-scale environments.
• 5+ years’ experience in architecting distributed cloud-native applications.
• 10+ years of software development experience.
• Experience with Computer Vision, Image Recognition, and related Machine Learning technologies.

Mandatory Tech Skills :

• Deep understanding and experience in Computer Vision technologies utilizing state-of-the-art techniques such as CNNs, R-CNN, YOLO, and OpenCV.
• Experience in developing and deploying image and video analysis algorithms.
• Experience in AI pipelines, AIOps, GPU architectures and optimizations including data preprocessing, feature extraction, model training, and evaluation.
• Proficiency in Python and experience with libraries and frameworks such as TensorFlow, PyTorch, and Keras.
• Expertise in Software as a Service and associated technologies.
• Familiarity with Kubernetes and Docker.
• Familiarity with Cloud infrastructure and Platforms - Azure /GCP/AWS.
• Experience in architecting solutions for public, private, hybrid, and multi-tenant environments.
• Excellent knowledge in architecting, designing, developing, and integrating of real-time communication applications.
• Excellent written and oral communication.
• Support the establishment of DevOps/SRE culture and methodologies within the organization.
• Collaboration with Other Solution Architects and remote teams.