About the Role

We are looking for a Senior Machine Learning Engineer with strong foundations in classical machine learning to design, build, and deploy scalable ML solutions that power data-driven products and platforms. This role involves owning the end-to-end ML lifecycle from data ingestion and feature engineering to model training, evaluation, and production deployment while collaborating closely with data engineering, platform, and product teams.

The ideal candidate is hands-on, production-oriented, and deeply experienced in regression, classification, and large-scale data processing, with working exposure to modern Generative AI and LLM platforms as an added advantage.

Roles & Responsibilities

• Design, develop, and deploy ML models for regression, classification, clustering, and anomaly detection use cases
• Build end-to-end ML pipelines including data extraction, ingestion, preprocessing, feature engineering, model training, and evaluation
• Work with structured and semi-structured data to enable scalable, high-performance ML systems
• Implement feature engineering, feature selection, normalization, and scaling techniques for robust model performance
• Deploy and monitor ML models in production using containerized and cloud-native approaches
• Collaborate with data engineering teams on ETL pipelines, data quality, and data availability
• Optimize model performance, reliability, and inference latency in real-world environments
• Contribute to MLOps practices including versioning, CI/CD, monitoring, and retraining workflows
• Leverage LLM-based solutions where appropriate (e.g., text classification, enrichment, or hybrid ML + LLM pipelines)

Skills & Knowledge

Requirements

• 3–5 years of experience building and deploying machine learning solutions in production environments
• Proven track record of delivering end-to-end ML projects from data to deployment
• Strong problem-solving mindset with the ability to translate business problems into ML solutions
• Experience working in cross-functional, data-driven teams

Education & Certification

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field
• Relevant certifications in ML, Data Engineering, or Cloud platforms are preferred but not mandatory

Preferred Certifications

• Machine Learning or AI certifications (AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer, Microsoft Azure AI Engineer Associate)
• Cloud or Big Data certifications are an added advantage