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Walk-in || AI/ML Engineer - Walk-in Drive on 27th June @ Chennai, WTC

  • Source: Naukri
  • Agilisium
  • On-site
  • Chennai
  • Full-Time
  • Mid level

Job Description

Calling AI Innovators!
If you’re passionate about Generative AI, LLMs, RAG, MLOps, and Machine Learning, this is your opportunity to join one of the fastest-growing AI-driven organizations.

Walk-In Drive: 27th June 2026 Chennai

Venue: Agilisium Consulting,World Trade Center 1st floor of Tower B, 5/142, Rajiv Gandhi Salai, Perungudi, Chennai, Tamil Nadu 600096

If Interested,Pls do register in below link without fail to initiate entry pass

https://agilisium.zohorecruit.com/jobs/Careers/589705000035867149/AI-ML-Engineer?source=CareerSite

Job Description:

Experience in Gen AI, CI/CD pipelines, scripting languages, and a deep understanding of version control systems(e.g. Git), containerization (e.g. Docker), and continuous integration/deployment tools (e.g. Jenkins) third party integration is a plus, cloud computing platforms (e.g. AWS, GCP, Azure), Kubernetes and Kafka.

  • Experience building production-grade ML pipelines.
  • Proficient in Python and frameworks like Tensorflow, Keras, or PyTorch.
  • Experience with cloud build, deployment, and orchestration tools
  • Experience with MLOps tools such as MLFlow, Kubeflow, Weights & Biases, AWS Sagemaker, Vertex AI, DVC, Airflow, Prefect, etc.,
  • Experience in statistical modeling, machine learning, data mining, and unstructured data analytics.
  • Understanding of ML Lifecycle, MLOps & Hands on experience to Productionize the ML Model
  • Detail-oriented, with the ability to work both independently and collaboratively.
  • Ability to work successfully with multi-functional teams, principals, and architects, across organizational boundaries and geographies.
  • Equal comfort driving low-level technical implementation and high-level architecture evolution
  • Experience working with data engineering pipelines

Skills

  • Docker
  • Jenkins
  • amazon-web-services
  • google-cloud-platform
  • microsoft-azure
  • Kubernetes
  • Kafka
  • Python
  • Tensorflow
  • Keras
  • PyTorch
  • ml-flow
  • mlflow
  • kubeflow
  • vertex
  • dvc
  • Airflow
  • apache-airflow
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