AI/ML Engineer
Agilisium
Description
WALK-IN DRIVE - AI/ML ENGINEER
DRIVE DATE : 13/12/2025
TIME : 11AM TO 3PM
LOCATION : World Trade Center 1st floor of Tower B, 5/142, Rajiv Gandhi Salai, Perungudi, Chennai, Tamil Nadu 600096
SKILL :Python, Tensorflow,Gen AI (Must Have), Machine learning ,AWS, Agentic AI, Claude, Fast API (Good to have)
EXP : 3 -10 yrs
Introduction to the Role:
Are you passionate about building intelligent systems that learn, adapt, and deliver real-world value? Join our high-impact AI & Machine Learning Engineering team and be a key contributor in shaping the next generation of intelligent applications. As an AI/ML Engineer, you'll have the unique opportunity to develop, deploy, and scale advanced ML and Generative AI (GenAI) solutions in production environments, leveraging cutting-edge technologies, frameworks, and cloud platforms.
In this role, you will collaborate with cross-functional teams including data engineers, product managers, MLOps engineers, and architects to design and implement production-grade AI solutions across domains. If you're looking to work at the intersection of deep learning, GenAI, cloud computing, and MLOps — this is the role for you.
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.
Essential Skills / Experience:
- 3–10 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
About Agilisium:
- 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.
- Our most important asset? People.
- Talent management plays a vital role in our business strategy.
About Agilisium
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