Overview

Senior Engineer - AI

Responsibilities

• Design, develop, and optimize machine learning models for applications across different domains.
• Apply supervised and unsupervised learning, deep learning, reinforcement learning, and other machine learning techniques.
• Develop NLP pipelines for language modelling, text generation, summarization, translation, and sentiment analysis.
• Build and deploy Generative AI applications, including conversational AI, text generation, and image synthesis.
• Develop real-world applications using Agentic AI frameworks such as LangGraph, ADK, and AutoGen.
• Implement MLOps practices covering model training, evaluation, deployment, monitoring, and maintenance.
• Process data, perform feature engineering, and train models on large datasets.
• Deploy scalable machine learning solutions using cloud platforms such as AWS, GCP, or Azure.
• Apply responsible AI practices, model governance, and risk mitigation measures.
• Follow software engineering best practices when developing and maintaining machine learning systems.

Qualifications

• Job Overview :
• We are looking for a Senior AI Engineer with strong expertise in machine learning, natural language processing, Generative AI, and Agentic AI.
• The role involves designing, developing, and deploying machine learning models and AI-powered applications, along with implementing MLOps practices to support model deployment, monitoring, and maintenance.
• Minimum 5 years of experience in machine learning engineering and AI development.
• Strong knowledge of machine learning algorithms, including supervised learning, unsupervised learning, deep learning, and reinforcement learning.
• Solid experience in Natural Language Processing (NLP), including language models, text generation, and sentiment analysis.
• Strong understanding of Generative AI concepts, including transformers, diffusion models, and text, image, and audio synthesis.
• Hands-on experience developing and deploying Generative AI and Agentic AI applications.
• Experience with Agentic AI frameworks such as LangGraph, ADK, or AutoGen.
• Proficiency in Python and machine learning frameworks such as TensorFlow and PyTorch.
• Experience with MLOps and machine learning model deployment pipelines.
• Knowledge of cloud platforms such as AWS, GCP, or Azure.
• Experience with data processing, feature engineering, and model training on large datasets.
• Familiarity with responsible AI, AI ethics, model governance, and risk mitigation.
• Understanding of software engineering best practices for machine learning systems