Computer Vision Technical Lead

Location: Hyderabad, Telangana, India

Workplace: on_site

Employment Type: full

Description

Job Description

Company Description:

Master Works is a Saudi-based company operating in multiple countries, specializing in emerging technologies in data and digital transformation. They empower customers through innovation and expertise in areas such as data management, AI, and computer vision, strategy management, middleware, and software development.

Experience: 8-12 years

Role: Technical Lead (CV/AI)

Location: Hyderabad (Work from office)

Working Days: Sunday to Thursday

Note: We are looking for a TL with minimum 8+ years of experience in CV/AI and 4+ years as a Technical Lead.

Responsibilities:

• Lead Development Efforts: Oversee and guide the development of computer vision solutions, ensuring high-quality, robust, and scalable algorithms and models.
• Architect Solutions: Design and architect complex systems involving real-world computer vision problems, integrating various technologies and platforms.
• Team Coordination: Collaborate with other researchers, engineers, and stakeholders to coordinate project activities, manage timelines, and ensure project milestones are met.
• Technical Leadership: Provide technical guidance and mentorship to team members, fostering an environment of continuous learning and improvement.
• Algorithm Development: Lead the creation of industry-grade algorithms using OpenCV, Python, and deep learning frameworks.
• Model Training and Evaluation: Oversee the training, evaluation, and fine-tuning of state-of-the-art deep learning models for tasks such as segmentation, object detection, classification, object tracking, visual style transfer, and generative adversarial networks.
• Integration and Deployment: Supervise the integration of models with various in-house and external microservices, ensuring seamless operation and deployment using technologies like Kubernetes, Docker, and containerization.
• Research and Innovation: Drive research into emerging technologies, developing proof of concepts (POCs) and evaluating their potential impact on existing and future projects.
• Project Planning and Management: Define the scope of work for computer vision research projects, including setting clear research objectives and outcomes.
• Technical Documentation: Prepare and maintain comprehensive technical documentation for algorithms, models, and deployment processes.
• Collaboration and Communication: Engage with cross-functional teams, including product managers and business stakeholders, to align on project goals and deliverables.
  

Requirements

• Leadership: Proven experience in leading technical teams, managing projects, and driving complex development efforts.
• C++ (Mandatory): Proficiency in C++ for implementing high-performance algorithms.
• Python (Mandatory): Expertise in Python for algorithm development and model training.
• Object Detection (Mandatory): In-depth knowledge and experience in object detection techniques and frameworks.
• Computer Vision (Mandatory): Strong background in computer vision principles, algorithms, and techniques.
• Image Processing (Mandatory): Advanced skills in image processing methods and their application in real-world scenarios.
• Deep Learning (Mandatory): Proficiency in deep learning technologies and frameworks such as Keras, TensorFlow, and PyTorch.
• NLP: Proficiency in NLP algorithms and models such as Text classification, Speech Recognition, Sentiment Analysis, Named Entity Recognition (NER).
• LLM: Proficiency in LLM such as BERT, PaLM, T5, GPT.
• AI and Machine Learning: Broad understanding of artificial intelligence, machine learning, and pattern recognition techniques.
• Data Science: Experience with data science principles and practices, including data manipulation and analysis.
• Generative Models: Familiarity with generative adversarial networks (GANs) and other generative models.
• Deployment Practices: Experience with deployment technologies and practices, including Kubernetes, Docker, and model compression techniques.