Machine Learning Engineer

Weekday AI (YC W21); Bengaluru; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

A technology consulting firm in Bengaluru is seeking a skilled Machine Learning Engineer to design, build, and scale production-ready ML systems. The role requires a strong software engineering background and hands-on experience with ML frameworks. Candidates should have at least 3 years of experience in the field, with a focus on developing efficient ML pipelines and APIs. This position offers the opportunity to work on innovative projects in the growing field of machine learning.

Qualifications

• 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.

Responsibilities

• Design and implement automated training and inference pipelines.
• Develop frameworks for on-demand model training.
• Design and develop robust APIs for ML capabilities.
• Build ETL pipelines and preprocessing frameworks tailored for ML applications.
• Implement comprehensive monitoring solutions for performance optimization.

Skills

Machine Learning

Python

TensorFlow

PyTorch

Scikit-learn

MLOps

Docker

Kubernetes

Cloud Platforms (AWS, GCP, Azure)

CI/CD

ETL Pipelines

Education

Bachelor's degree in Computer Science, Engineering, or a related field

Tools

TensorFlow

Docker

Kubernetes

Job description

Machine Learning Engineer

This role is for one of the Weekday's clients

Min Experience: 3 years
Location: Bangalore
Job Type: 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

Seniorities

• Associate

Employment Type

• Full‑time

Job Function

• Other

Industries

• IT Services and IT Consulting