Machine Learning Engineer

Grid Dynamics; Bengaluru; On-site; INR 800,000 - 1,200,000; Full time

Benefits offered by this job

Competitive salary

Medical insurance

Flexible schedule

Professional development opportunities

Corporate social events

Job summary

Grid Dynamics is hiring for a machine learning engineer in Bangalore, India. The role involves designing and optimizing machine learning models, collaborating with teams, and ensuring the implementation of MLOps best practices. You will have the opportunity to work on cutting-edge projects and contribute to the team's knowledge and skills.

The ideal candidate should have over 4 years of experience in machine learning, model development, and feature engineering. The position offers a competitive salary, flexible schedule, and a comprehensive benefits package.

Qualifications

• 4+ years of experience in machine learning.
• Experience in developing and maintaining end-to-end ML pipelines.
• Ability to monitor, retrain models, and improve accuracy.

Responsibilities

• Design and build machine learning models for various business use cases.
• Collaborate with cross-functional teams to translate requirements into ML solutions.
• Implement best practices for scalability, security, and governance.

Skills

ML modelling

Machine Learning

MLOps

Feature engineering

Data security

Job description

Total Experience - 4 Years and above

Location- Bangalore

Notice Period - Max 15 days

Job Description

• Design, build, train, evaluate, and optimize machine learning models for a variety of business use cases.
• Develop and maintain end-to-end ML pipelines for data preparation, feature engineering, model training, validation, and deployment.
• Leverage the Machine Learning Platform (MLP) to accelerate model development and experimentation.
• Collaborate with data scientists and cross‑functional teams to translate business requirements into machine learning solutions.
• Monitor model performance, retrain models as needed, and continuously improve model accuracy and efficiency.
• Ensure ML solutions follow best practices for scalability, security, reproducibility, and governance.
• Document model development processes, experiments, and deployment procedures.
• Stay current with emerging machine learning techniques, tools, and industry best practices.

Essential functions

• Develop and maintain feature engineering pipelines and model versioning strategies.
• Monitor deployed models for performance, drift, and reliability, retraining models as needed.
• Implement MLOps best practices, including CI/CD for machine learning workflows.
• Optimize algorithms for scalability, latency, and resource utilization.
• Conduct experiments and A/B testing to validate model effectiveness.
• Ensure data security, privacy, and compliance with organizational and regulatory standards.
• Document model architectures, experiments, and deployment processes.
• Stay current with advancements in machine learning, artificial intelligence, and cloud technologies.
• Troubleshoot production issues related to machine learning services and pipelines.
• Mentor junior engineers and contribute to technical knowledge sharing within the team.

Qualifications

ML modelling

We offer

• Opportunity to work on bleeding‑edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well‑equipped office