Machine Learning Engineer

8 hours ago

Bengaluru, Karnataka, India Weekday AI Full time

This role is for one of the Weekday's clients

Min Experience: 3 years

Location: Bangalore

JobType: full-time

We are seeking a highly skilled Machine Learning Engineer to design, build, and scale production-ready ML systems. The ideal candidate will have a strong software engineering background, hands-on experience with ML frameworks, and a deep understanding of MLOps principles. You will be responsible for architecting model training, inference, and deployment pipelines that enable efficient experimentation and reliable performance at scale.

What You'll Do

  • Design and implement automated training and inference pipelines, including building a model registry system for artifact tracking, versioning, and lineage.
  • Develop frameworks for on-demand model training and architect parallel processing systems to support inference in event-driven environments.
  • Design and develop robust APIs that expose machine learning capabilities for internal and external use.
  • Build ETL pipelines and preprocessing frameworks tailored for ML applications.
  • Implement comprehensive monitoring solutions to identify performance bottlenecks and optimize system scalability.
  • Create infrastructure to support offline and online experimentation.
  • Build internal tools and frameworks that standardize ML workflows across teams and improve efficiency.
  • Stay up to date with emerging trends in machine learning engineering and MLOps, and evaluate new tools and best practices.
  • Contribute to technical architecture and decision-making to enhance ML infrastructure and platform capabilities.

Required Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
  • 3+ years of experience in software engineering with a focus on machine learning systems.
  • Strong programming skills in Python and proficiency with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Hands-on experience building and maintaining production-grade ML pipelines.
  • Proficiency with containerization tools like Docker and Kubernetes.
  • Experience working with cloud platforms (AWS, GCP, or Azure) and their ML services.
  • Strong understanding of software engineering best practices, including version control, CI/CD, and testing.
  • Experience with data processing frameworks for large-scale data workflows.
  • Excellent problem-solving skills and the ability to work independently on complex technical challenges.
  • Strong communication and collaboration skills to work effectively with cross-functional teams.

Key Skills
Machine Learning | Python | TensorFlow | PyTorch | Scikit-learn | MLOps | Docker | Kubernetes | Cloud Platforms (AWS/GCP/Azure) | CI/CD | ETL Pipelines

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