AI/ML Engineer

Agilisium Technologies LLC.; Chennai District; On-site; INR 800,000 - 1,500,000; Full time

Benefits offered by this job

Certification programs

Continuous learning opportunities

Dynamic work environment

Job summary

A leading technology solutions provider in Chennai is seeking a skilled professional to design and deploy advanced ML and GenAI models. You will leverage cloud platforms and cutting-edge frameworks like TensorFlow and PyTorch to build scalable deep learning solutions. The ideal applicant will have a strong programming background in Python with 2-10 years of experience. The role involves collaborating with diverse teams and implementing CI/CD processes for effective ML governance. Join us to innovate and drive impactful AI-driven transformations.

Qualifications

• 2–10 years of experience in ML/DL/GenAI model development.
• Strong programming expertise in Python.
• Familiarity with CI/CD tools such as Jenkins or GitHub Actions.
• Experience with MLOps best practices.
• Solid understanding of statistical modeling and machine learning algorithms.

Responsibilities

• Design and deploy ML and GenAI models across various use cases.
• Develop end-to-end ML pipelines for data ingestion and model training.
• Collaborate with data engineers to prepare datasets for ML.
• Implement CI/CD pipelines for efficient ML workload delivery.
• Build robust monitoring and retraining workflows for production models.

Skills

Python

Machine Learning

Data Manipulation

Scripting

Deep Learning Frameworks

Generative AI

Large Language Models (LLMs)

CI/CD Pipelines

Containerization

Cloud Platforms

Data Engineering Concepts

Tools

TensorFlow

Keras

PyTorch

LangChain

Docker

Kubernetes

AWS

GCP

Azure

MLflow

Kubeflow

Weights & Biases

Airflow

DVC

Prefect

Job description

F2F Walkin Drive - 14th Feb 2026
Location: Hyderabad

Accountabilities:

Design, develop, train, and deploy production-grade ML and GenAI models across use cases including NLP, computer vision, and structured data modeling.

Leverage frameworks such as TensorFlow, Keras, PyTorch, and LangChain to build scalable deep learning and LLM-based solutions.

Develop and maintain end-to-end ML pipelines with reusable, modular components for data ingestion, feature engineering, model training, and deployment.

Implement and manage models on cloud platforms such as AWS, GCP, or Azure using services like SageMaker, Vertex AI, or Azure ML.

Apply MLOps best practices using tools like MLflow, Kubeflow, Weights & Biases, Airflow, DVC, and Prefect to ensure scalable and reliable ML delivery.

Incorporate CI/CD pipelines (using Jenkins, GitHub Actions, or similar) to automate testing, packaging, and deployment of ML workloads.

Containerize applications using Docker and orchestrate scalable deployments via Kubernetes.

Integrate LLMs with APIs and external systems using LangChain, Vector Databases (e.g., FAISS, Pinecone), and prompt engineering best practices.

Collaborate closely with data engineers to access, prepare, and transform large-scale structured and unstructured datasets for ML pipelines.

Build monitoring and retraining workflows to ensure models remain performant and robust in production.

Evaluate and integrate third-party GenAI APIs or foundational models where appropriate to accelerate delivery.

Maintain rigorous experiment tracking, hyper parameter tuning, and model versioning.

Champion industry standards and evolving practices in ML lifecycle management, cloud-native AI architectures, and responsible AI.

Work across global, multi-functional teams, including architects, principal engineers, and domain experts.

2–10 years of hands‑on experience in developing, training, and deploying ML/DL/GenAI models.

Strong programming expertise in Python with proficiency in machine learning, data manipulation, and scripting.

Demonstrated experience working with Generative AI models and Large Language Models (LLMs) such as GPT, LLaMA, Claude, or similar.

Hands‑on experience with deep learning frameworks like TensorFlow, Keras, or PyTorch.

Experience in LangChain or similar frameworks for LLM-based app orchestration.

Proven ability to implement and scale CI/CD pipelines for ML workflows using tools like Jenkins, GitHub, GitLab, or Bitbucket Pipelines.

Familiarity with containerization (Docker) and orchestration tools like Kubernetes.

Experience working with cloud platforms (AWS, Azure, GCP) and relevant AI/ML services such as SageMaker, Vertex AI, or Azure ML Studio.

Knowledge of MLOps tools such as MLflow, Kubeflow, DVC, Weights & Biases, Airflow, and Prefect.

Strong understanding of data engineering concepts, including batch/streaming pipelines, data lakes, and real-time processing (e.g., Kafka).

Solid grasp of statistical modeling, machine learning algorithms, and evaluation metrics.

Experience with version control systems (Git) and collaborative development workflows.

Ability to translate complex business needs into scalable ML architectures and systems.

Why Join Us?

Build and deploy cutting‑edge LLM and GenAI applications that solve real‑world problems.

Collaborate with thought leaders across engineering, product, and data science.

Work in a dynamic, cloud‑native, and automation‑driven AI environment.

Accelerate your growth through certification programs and continuous learning.

Be part of an innovation‑first team that values openness, agility, and integrity.

• Agilisium is an AWS technology Advanced Consulting Partner that enables companies to accelerate their "Data-to-Insights-Leap.
• With $50+ million in annual revenue and over 30% year-over-year growth, Agilisium is one of the fastest-growing IT solution providers in Southern California.
• Talent management plays a vital role in our business strategy.