# Machine Learning Engineer

> Weekday AI · Bengaluru, India · Full-time · Posted 2026-08-24

**Salary:** INR 400,000–1,000,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

**This role is for one of Weekday’s clients  
Salary range: Rs 400000 - Rs 1000000 (ie INR 4 - 10 LPA)**

  
Min Experience: 3+ years  
Location: Bengaluru, Karnataka, India  
JobType: full-time

We are looking for a skilled **Machine Learning Engineer** with 3–8 years of experience to design, develop, deploy, and optimize machine learning solutions that solve real-world business problems. The ideal candidate will have strong expertise in **Python** and a solid understanding of machine learning workflows, data processing, model development, and production deployment.

You will work closely with data scientists, software engineers, product teams, and other stakeholders to transform machine learning models and experimentation into reliable, scalable production systems.

## Requirements

### Key Responsibilities

-   Design, develop, train, evaluate, and optimize machine learning models using Python.
-   Build scalable and maintainable machine learning pipelines for data preparation, model training, validation, and deployment.
-   Develop clean, efficient, and production-ready Python code for machine learning applications.
-   Analyze large datasets, identify relevant patterns, and develop models that address business and product requirements.
-   Collaborate with data scientists and engineering teams to productionize machine learning models.
-   Implement model monitoring, evaluation, and performance optimization practices.
-   Troubleshoot issues across machine learning pipelines and production environments.
-   Develop APIs and services to integrate machine learning models into existing applications and platforms.
-   Follow software engineering best practices, including version control, testing, documentation, code reviews, and CI/CD.
-   Continuously evaluate new machine learning techniques, frameworks, and tools to improve system performance and reliability.

### Must-Have Skills

-   **3–8 years of professional experience** in machine learning engineering, data science, software engineering, or a closely related field.
-   Strong programming skills in **Python** with experience writing production-quality code.
-   Strong understanding of machine learning concepts, algorithms, model evaluation, and optimization.
-   Hands-on experience with machine learning frameworks such as **Scikit-learn, PyTorch, TensorFlow**, or equivalent.
-   Experience with data preprocessing, feature engineering, model training, validation, and deployment.
-   Understanding of software development practices, APIs, testing, Git, and version control.
-   Ability to work with cross-functional teams and translate business requirements into scalable technical solutions.
-   Strong problem-solving, analytical, and debugging skills.

### Good-to-Have Skills

-   Experience working with **Google Cloud Platform (GCP)** and cloud-based machine learning infrastructure.
-   Hands-on experience with **Kubernetes** for deploying and managing containerized machine learning workloads.
-   Experience with **Terraform** or other Infrastructure-as-Code tools for automating cloud infrastructure.
-   Familiarity with Docker, CI/CD pipelines, and cloud-native development practices.
-   Experience building scalable ML services and production inference pipelines.
-   Understanding of MLOps practices, model monitoring, experiment tracking, and automated model deployment.
-   Exposure to distributed computing, data engineering, or large-scale machine learning systems.

### What We Offer

This role provides an opportunity to work on challenging machine learning problems while contributing to the development of scalable, production-grade AI systems. You will have the opportunity to work with modern cloud and infrastructure technologies and collaborate with experienced engineering and data teams.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/A43946A289/apply)

---
Powered by [Workable](https://www.workable.com)