Machine Learning Engineer
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
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.Apply to the position
Information on personal data processing
You cannot apply for a position without accepting “INFORMATION ON PERSONAL DATA PROCESSING”
Applications for this job are no longer accepted. Please explore other open opportunities on our platform.
Thank you!
You applied for the position Machine Learning Engineer successfully. We will get back to you soon. Have a great day!
Something went wrong...
There are possible difficulties with connection or other issues. Please try to use another browser (it's recommended to use the latest version of Google Chrome browser). If the problem still persists, please send your application to cv@griddynamics.com
RetrySomething went wrong...
Please double-check the information filled in the form, and make sure to provide valid data.
RetryDon’t see the right opportunity?
Contact us anyway and let’s talk! To apply, send your resume and cover letter to jobs@griddynamics.com
Grid Dynamics is an equal opportunity employer. We are committed to creating an inclusive environment for all employees during their employment and for all candidates during the application process.
All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. All employment is decided on the basis of qualifications, merit, and business need.