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
- Market-competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office

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