Analytics Machine Learning

5 days ago

New Delhi, India Tata Consultancy Services Full time

Job Title: Analytics/ ML Technical Lead

Location : New Delhi

Experience Level: 8+ years

Job Overview:

We are looking for a highly skilled Analytics Machine Learning Expert with hands on experience in opensource AI/ML tools and technologies to build and deploy machine learning models that drive key business insights. The ideal candidate will be technically proficient in implementing scalable machine learning solutions using opensource frameworks, with a deep understanding of data science, analytics, and model operationalization.

Key Responsibilities:

  • Machine Learning Model Development: Architect and develop complex machine learning models (supervised, unsupervised, deep learning) using opensource frameworks such as TensorFlow, PyTorch, and scikitlearn.
  • OpenSource AI/ML Expertise: Leverage opensource AI/ML tools and libraries to build, train, and deploy models, ensuring efficient use of resources and adherence to best practices.
  • Data Wrangling & Feature Engineering: Perform data cleaning, transformation, and feature engineering to prepare largescale datasets for model training and improve prediction accuracy.
  • Model Deployment & Automation: Implement models in production environments using opensource tools and frameworks, with a focus on automation, reproducibility, and scaling. Utilize tools such as Kubeflow, MLflow, or Seldon for MLOps.
  • Performance Tuning & Optimization: Continuously evaluate model performance and refine algorithms for scalability, efficiency, and accuracy. Use techniques like hyperparameter tuning and distributed training.
  • Collaboration: Collaborate with data engineers and architects to design and optimize data pipelines, ensuring smooth integration of machine learning models into broader analytics platforms.
  • Research & Innovation: Stay updated on cuttingedge advancements in AI/ML, exploring how opensource innovations can be integrated into current architectures for improved outcomes.
  • Cloud & Distributed Computing: Implement scalable solutions using cloudnative services (AWS, GCP, Azure) and distributed computing frameworks like Apache Spark and Hadoop to handle large data volumes.

Advanced Analytics: Develop predictive and prescriptive analytics models that solve complex business problems, utilizing advanced statistical methods and deep learning architectures

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