Gen AI Engineer

About the Role

• Be a hands-on problem solver with a consultative approach, applying Machine Learning & Deep Learning algorithms to solve business challenges.
• Use knowledge of a wide variety of AI/ML techniques and algorithms to find the best combinations to solve problems.
• Improve model accuracy to deliver greater business impact.
• Estimate business impact due to model deployment.

Key Responsibilities

• Work with domain/customer teams to understand business context and data dictionaries, applying relevant Deep Learning solutions.
• Use tools and scripts for pre-processing data and feature engineering for model development, including Python / R / SQL / Cloud data pipelines.
• Design, develop, and deploy Deep Learning models using Tensorflow / Pytorch.
• Experience using Deep Learning models with text, speech, image, and video data.
• Design and develop NLP models for Text Classification, Custom Entity Recognition, Relationship Extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and open-source Tensorflow, Pytorch.
• Design and develop Image recognition & video analysis models using Deep learning algorithms and open-source tools like OpenCV.
• Optimize and tune Deep Learning models for best possible accuracy.
• Use visualization tools/modules (e.g., Power BI / Tableau) to explore and analyze outcomes and for model validation.
• Work with application teams to deploy models on the cloud as a service or on-premise.
• Deploy models in a Test / Control framework for tracking.
• Build CI/CD pipelines for ML model deployment.
• Integrate AI&ML models with other applications using REST APIs and other connector technologies.
• Continuously upskill and update with the latest techniques and best practices.
• Write white papers and create demonstrable assets to summarize AIML work and its impact.

Technology/Subject Matter Expertise

• Sufficient expertise in machine learning, mathematical and statistical sciences.
• Use of versioning & collaborative tools like Git / Github.
• Good understanding of the landscape of AI solutions, including cloud, GPU-based compute, data security and privacy, API gateways, microservices-based architecture, big data ingestion, storage and processing, and CUDA Programming.
• Develop prototype-level ideas into solutions that can scale to industrial-grade strength.
• Ability to quantify and estimate the impact of ML models.

Soft Skills Profile

• Curiosity to think in fresh and unique ways with the intent of breaking new ground.
• Ability to share, explain, and sell thoughts, processes, ideas, and opinions, even outside their own span of control.
• Ability to think ahead and anticipate needs for solving problems.
• Ability to communicate key messages effectively and articulate strong opinions in large forums.

Desirable Experience

• Keen contributor to open-source communities and communities like Kaggle.
• Ability to process huge amounts of data using Pyspark/Hadoop.
• Development & Application of Reinforcement Learning.
• Knowledge of Optimization/Genetic Algorithms.
• Operationalizing Deep Learning models for a customer and understanding nuances of scaling such models in real scenarios.
• Understanding of stream data processing, RPA, edge computing, AR/VR.
• Appreciation of digital ethics and data privacy.
• Experience working with AI & Cognitive services platforms like Azure ML, IBM Watson, AWS Sagemaker, Google Cloud.
• Experience with platforms like Data robot, Cognitive scale, H2O.AI.