Senior AI/ML Engineer role at Agilisium, Chennai. Lead production ML pipelines, Gen AI integration, and MLOps.

About the Company

Agilisium is a premier IT services and consulting firm headquartered in Chennai, Tamil Nadu. With a strong focus on data engineering, AI/ML, and cloud solutions, Agilisium partners with global enterprises to accelerate their digital transformation. The company fosters a collaborative culture and values technical excellence, enabling teams to work on cutting-edge projects across industries. Agilisium’s team of engineers and architects brings deep expertise in building scalable, production-grade systems, making it an ideal workplace for senior AI/ML professionals seeking challenging roles.

Role Overview

As a Senior AI/ML Engineer at Agilisium, you will lead the design, development, and deployment of advanced machine learning models and AI systems. You will be responsible for building end-to-end ML pipelines, integrating generative AI capabilities, and ensuring that models are efficiently productionized using MLOps best practices. This role requires a strong blend of software engineering and data science skills, with a focus on scalability, reliability, and performance. You will collaborate with cross-functional teams, including data engineers, architects, and product managers, to deliver high-impact solutions that drive business outcomes. The position demands a proactive, detail-oriented candidate who is comfortable operating at both the architectural and implementation levels.

Key Responsibilities

• Design and implement production-grade ML pipelines, from data ingestion to model deployment and monitoring.
• Build and maintain CI/CD pipelines for machine learning models, leveraging tools like Jenkins, Git, Docker, and Kubernetes.
• Integrate generative AI technologies (e.g., LLMs, RAG) into enterprise applications.
• Containerize ML workloads and orchestrate them using Kubernetes and Kafka for real-time data streaming.
• Utilize cloud platforms (AWS, GCP, or Azure) for model training, deployment, and scaling.
• Employ MLOps frameworks such as MLFlow, Kubeflow, Weights & Biases, SageMaker, Vertex AI, and Airflow to manage the ML lifecycle.
• Perform statistical modeling, machine learning, data mining, and analysis of unstructured data.
• Work closely with data engineering teams to build robust data pipelines.
• Participate in code reviews, architecture discussions, and technical strategy planning.
• Mentor junior engineers and contribute to the continuous improvement of AI/ML practices.

Tech Stack

• Languages: Python
• ML/DL Frameworks: TensorFlow, Keras, PyTorch
• Cloud Platforms: AWS, GCP, Azure (with specific services like SageMaker, Vertex AI)
• Containerization & Orchestration: Docker, Kubernetes, Kafka
• CI/CD & Version Control: Jenkins, Git
• MLOps Tools: MLFlow, Kubeflow, Weights & Biases, DVC, Airflow, Prefect
• Data Engineering: Pipelines for structured/unstructured data, data mining
• Other: Statistical modeling, Gen AI (LLMs), third-party integrations, CI/CD scripting

5+ years of experience in AI/ML engineering, strong Python skills, production ML pipeline experience, proficiency in MLOps and cloud platforms.

Competitive salary, health insurance, professional development opportunities.