Senior AIML Engineer

Litmus7 seeks a Senior AIML Engineer in Kochi or Bangalore to develop and deploy machine learning, deep learning, generative AI, and agentic AI applications across different domains. The role covers the end-to-end ML lifecycle, from data preparation and model development through production deployment and monitoring.

Responsibilities

• Design, develop, and optimize ML models; build NLP pipelines for text generation, summarization, and translation; and develop and deploy generative and agentic AI applications.
• Integrate ML capabilities into existing products or create new AI-powered applications. Mine, clean, prepare, and augment data for robust model training.
• Implement MLOps practices for training, evaluation, deployment, monitoring, and maintenance. Ensure model performance, scalability, and reliability.
• Collaborate with cross-functional teams to turn AI requirements into technical implementations, and research and apply current AI/ML algorithms and techniques.

Requirements

• At least 5 years of experience in machine learning engineering and AI development, with hands-on ML, deep learning, generative AI, and deployment experience. A bachelor’s or master’s degree in computer science, AI, statistics, mathematics, or a related field.
• Deep knowledge of supervised and unsupervised learning, deep learning, and reinforcement learning; NLP experience with language models, text generation, and sentiment analysis; and understanding of generative techniques including text, image, and audio synthesis, diffusion models, and transformers.
• Experience building real-world agentic AI applications with frameworks such as LangGraph, ADK, or AutoGen, and developing and deploying generative applications including text generation, conversational AI, or image synthesis.
• Proficiency in Python and ML frameworks such as TensorFlow or PyTorch; experience with MLOps and model deployment pipelines, cloud platforms such as AWS, GCP, or Azure, and large-dataset processing, feature engineering, and model training.
• Familiarity with responsible AI, ethics, governance, and risk mitigation; software engineering best practices for ML systems; agile development; and tools for monitoring model performance and data accuracy. Strong problem-solving, analytical, and communication abilities are required.