Machine Learning Engineer III

Location:

Employment Type: Full-timeExperience Level: 6+ years overall | 4+ years in developmentCTC: Up to 24 LPA

Machine Learning Engineer (Engineer III)

production-grade, self-running ML solutions

• Collaborate with business and technical stakeholders to understand current and future machine learning requirements
• Design and develop advanced ML models and algorithms to solve complex problems across structured and unstructured data
• Build, maintain, and optimize scalable ML pipelines, architectures, and infrastructure
• Apply machine learning and statistical techniques such as decision trees, logistic regression, Bayesian analysis, and related methods to improve system performance, quality, and accuracy
• Implement ML solutions across domains including object detection, tracking, classification, perception, localization, and spatial/terrain mapping
• Train, retrain, and fine-tune ML models as required to meet evolving business needs
• Deploy ML models into production environments and run simulations to validate algorithms under multiple scenarios
• Automate model training, deployment, and retraining using CI/CD/CT practices and MLOps frameworks
• Enable robust model management, including versioning, traceability, and lifecycle governance across environments
  

Required Skills

• Strong experience in AI/ML engineering
• Hands-on expertise with Python-based ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience working with BigQuery or large-scale data platforms
• Proficiency in building and maintaining production-ready ML pipelines
  

Preferred Skills

• Frontend or full-stack software engineering experience
• Exposure to Java-based full-stack development
• Experience integrating ML models with web or enterprise applications
  

Frontend & Application Integration

• Experience with modern frontend frameworks such as React or Angular
• Ability to build responsive, scalable, and intuitive UI components
• Strong experience integrating APIs and visualizing ML outputs in applications
  

Machine Learning & MLOps

• Data preprocessing, model training, evaluation, and deployment expertise
• Understanding of MLOps practices for monitoring, scaling, and maintaining ML solutions in production
  

System Integration

• Ability to embed ML models into applications for real-time or near-real-time predictions
• Experience building workflows connecting backend services, ML pipelines, and frontend interfaces
• Strong debugging, performance tuning, and optimization skills across ML and software layers
  

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