Senior AIML Engineer

Litmus7 Systems Consulting Ltd; Ernakulam, Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

Litmus7 Systems Consulting Ltd is seeking a Senior AIML Engineer with hands-on experience in ML, DL and Gen AI with deployment. You will design, develop and deploy scalable AI models across domains, with emphasis on NLP and agentic AI.

You will own the ML lifecycle from data processing to production, implement MLOps, and collaborate with cross-functional teams. Proficiency in Python, TensorFlow or PyTorch, and cloud platforms is essential; a strong background in responsible AI and governance is

Qualifications

• At least 5 years of ML engineering/AI development experience.
• Deep expertise in ML algorithms incl. supervised/unsupervised, DL, RL.
• Solid NLP experience: language models, text generation, sentiment analysis.
• Experience with generative AI concepts like diffusion models and transformers.
• Expertise in Agentic AI and real-world applications.
• Hands-on with Agentic AI frameworks like Langgraph, ADK, Autogen.
• Proficient in Python; TensorFlow or PyTorch.
• Cloud experience on AWS/GCP/Azure for scalable deployment.
• Familiarity with responsible AI, governance and risk mitigation.
• Strong communication and teamwork; agile environment.

Responsibilities

• Design, develop and optimize ML models for applications across domains.
• Build NLP pipelines for tasks like text generation, summarization, translation.
• Develop and deploy cutting-edge generative AI & Agentic AI applications.
• Implement MLOps practices - training, evaluation, deployment, monitoring, maintenance.
• Integrate ML capabilities into existing products or new AI-powered apps.
• Perform data mining, cleaning, preparation, and augmentation for training robust models.
• Collaborate with cross-functional teams to translate AI requirements into implementations.
• Continuously research and implement state-of-the-art AI/ML algorithms and techniques.
• Manage the end-to-end ML lifecycle from data processing to production deployment.

Skills

ML & AI engineering

NLP & language models

Generative AI

Agentic AI

MLOps

Python

Data processing

Model governance

Agile methodologies

Problem solving

Education

Bachelor's or Master's in CS/AI/Statistics/Math

Tools

Langgraph

ADK

Autogen

TensorFlow

PyTorch

AWS

GCP

Azure

Job description

We are looking for a Senior AIML Engineer with good hands on experience in ML, DL and Gen AI with deployment.

• Minimum 5 years of experience in machine learning engineering and AI development.
• Deep expertise in machine learning algorithms and techniques like supervised/unsupervised learning, deep learning, reinforcement learning, etc.
• Solid experience in natural language processing (NLP) - language models, text generation, sentiment analysis, etc.
• Proven understanding of generative AI concepts like text/image/audio synthesis, diffusion models, transformers, etc.
• Expertise in Agentic AI and building real world applications using the same.
• Experience working with Agentic AI frameworks like Langgraph, ADK, Autogen etc.
• Hands‑on experience developing and deploying generative AI applications (text generation, conversational AI, image synthesis, etc.)
• Experience in MLOps and ML model deployment pipelines.
• Proficiency in programming languages like Python, and ML frameworks like TensorFlow, PyTorch, etc.
• Knowledge of cloud platforms (AWS, GCP, Azure) and tools for scalable ML solution deployment.
• Experience with data processing, feature engineering, and model training on large datasets.
• Familiarity with responsible AI practices, AI ethics, model governance and risk mitigation.
• Understanding of software engineering best practices and applying them to ML systems.
• Experience with an agile development environment.
• Exposure in tools/framework to monitor and analyse ML model performance and data accuracy.
• Strong problem-solving, analytical, and communication abilities.
• Bachelor’s or master’s degree in computer science, AI, Statistics, Math or related fields.

Responsibilities:

• Design, develop and optimize machine learning models for applications across different domains.
• Build natural language processing pipelines for tasks like text generation, summarization, translation, etc.
• Develop and deploy cutting‑edge generative AI & Agentic AI applications.
• Implement MLOps practices - model training, evaluation, deployment, monitoring, and maintenance.
• Integrate machine learning capabilities into existing products or build new AI‑powered applications.
• Perform data mining, cleaning, preparation, and augmentation for training robust ML models.
• Collaborate with cross‑functional teams to translate AI requirements into technical implementations.
• Continuously research and implement state‑of‑the‑art AI/ML algorithms and techniques.
• Manage the end‑to‑end ML lifecycle from data processing to production deployment.