Ml Engineer

1 day ago

Bengaluru, Karnataka, India Aziro Full time ₹ 1,20,000 - ₹ 1,80,000 per year

We are looking for Machine Learning Experts - Immediate Joiners for Bangalore location

Exp - 5+ years

Location - Bangalore

Job Description :

Overview

We're looking for a highly motivated Machine Learning Engineer (MLE) to design, build, and deploy robust and scalable machine learning models. You'll work closely with data scientists, data engineers, and product managers to translate complex business problems into high-impact ML solutions that drive product value.

Key Roles and Responsibilities

The primary responsibilities of the Machine Learning Engineer include:

1. Model Development and Implementation

  • Design and build machine learning systems, pipelines, and APIs.
  • Research and implement appropriate ML algorithms and tools, from classical methods to deep learning, for specific tasks.
  • Train, test, and tune machine learning models using large datasets.

2. Production and Deployment (MLOps)

  • Deploy models into a production environment, ensuring high performance, scalability, and reliability.
  • Monitor the performance of models in production and implement strategies for continuous improvement and retraining.
  • Develop tools and infrastructure to automate model building, deployment, and monitoring (CI/CD for ML).

3. Collaboration and Data Management

  • Collaborate with data scientists to transition prototypes into production-ready code.
  • Work with data engineers to establish robust data pipelines for model training and inference.
  • Ensure data quality, cleanliness, and availability for training and testing purposes.

4. Optimization and Maintenance

  • Optimize model performance for speed and efficiency in production.
  • Troubleshoot and resolve issues related to model performance, data flow, and infrastructure.
  • Stay updated on the latest ML advancements, tools, and best practices.

Qualifications (Preferred)

  • Solid understanding of machine learning principles, statistics, and algorithms.
  • Proficiency in programming languages like Python (and libraries such as TensorFlow, PyTorch, or scikit-learn).
  • Experience with cloud platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
  • Experience in MLOps tools and practices.
  • Strong communication and teamwork skills.

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