AI ML - Computer Vision -Lead

Role:

The role is to lead the AI team by designing and developing scalable solutions using AI tools.

To turn business requirements into analytical questions effectively and provide meaningful recommendations.

Perform research and testing to develop machine learning algorithms and predictive models.

Solution the Data Pipeline Management (DPM) for respective UseCases.

As a Lead AI Engineer one needs to test tune integrate package and monitor solutions throughout the ML Cycle.

Guide the AI/ML Engineers on their daily tasks and help them solve any challenges they encounter technically.

Come up with post production activities to monitor the model decay data drift and apply Retraining approaches to ensure respective KPI s are constantly met.

Track daily progress from a solution standpoint. Identify risks and mitigate them.

Responsibilities:

Deliver robust welltested and fully documented modules to serve the use cases

Learn and implement stateoftheart deep learning algorithms to support people and product association

Collaborate with system architects designers and engineers to support the development of robust machine learning systems

Continuously improve the efficiency and robustness of existing modules

Work with Product Management to prioritize feature development

Work with engineering team to implement the entire application modules as discoverable microservices experience hosting and deploying ML solutions

Perform code reviews and ensuring proper design and delivery

Promote best practices and establishing team processes

Identify infrastructure and architectural investment needs

Requirements

Qualifications:

Overall 10 years of industry work experience in computer vision object detection pattern recognition artificial intelligence automation and/or vision processing.

5 years of relevant experience as a CV Engineer Data Scientist Machine Learning Engineer or related role.

Experience with common languages (e.g. Python SQL) and tools (e.g. TensorFlow PyTorch distributed training / inference with Spark) in the ML toolkit.

Knowledge of CUDA OpenCL OpenGL and OpenCV

Proficient in at least one of: PyTorch (Preferable) TensorFlow and Keras

Coding experience in programming Languages: Python (definite) Nodejs Javascript or Java

Experience with designing and developing popular highly scalable distributed ML models and opensource projects.

Knowledge of text detection & OCR human / face detection generative models video analytics model compression / optimization.

NLP techniques to process text image processing techniques and perform entity extraction

Very good understanding and knowledge of Statistical and ML Concepts:

Statistics

EDA (Univariate/ Bivariate/ Multivariate Analysis)

Hypothesis Testing

Regression/ Classification and Unsupervised Approaches

Algorithms (Generic and Bayseian)

Ensemble approaches

Evaluation techniques

Familiarity with various operating systems (e.g. Windows UNIX) and databases (e.g. MySQL)

Must have worked on MLOps Tools: MLFlow Kubeflow DVC etc.

Deploying code on one of the:

Cloud Platforms Azure AWS GCP.

Standalone Systems (Using Flask/ FastAPI/ Docker/ Kubernetes etc.)

Handling Code with respect to various languages PMML Pickle ONNX etc.

Good team player and excellent written and verbal technical communication skills

MS / PhD in engineering or quantitative discipline (e.g. Statistics Mathematics Computer Science etc.)

Benefits