Machine Learning Engineer

Machine Learning Engineer

Location: Bangalore (2 days/office)

Experience: 8+ Years

Employment Type: Contract

Role Overview

We are looking for an expert-level Machine Learning Engineer with strong hands-on expertise in Python to design, build, deploy, and optimize production-grade ML systems. The ideal candidate should combine deep ML knowledge with strong software engineering, system design, and MLOps capabilities.

Mandatory Skills

• 8+ years of professional experience in Machine Learning / ML Engineering.

• Expert-level Python programming skills.

• Strong understanding of Machine Learning algorithms, statistics, model evaluation, and feature engineering.

• Hands-on experience with scikit-learn, Pandas, NumPy, and ML frameworks such as PyTorch or TensorFlow.

• Strong experience building production-grade ML pipelines and inference systems.

• Solid understanding of MLOps, model deployment, monitoring, and lifecycle management.

• Strong knowledge of data structures, algorithms, software engineering, and system design.

• Experience working with SQL and large-scale datasets.

Key Responsibilities

• Design, develop, and optimize machine learning models and production ML systems using Python.

• Own the end-to-end ML lifecycle including data preparation, feature engineering, model

development, evaluation, deployment, and monitoring.

• Build scalable ML pipelines and inference services for production environments.

• Apply appropriate ML, statistical, and optimization techniques to solve complex business problems.

• Improve model accuracy, latency, scalability, and reliability through experimentation and

performance optimization.

• Collaborate with Data Scientists, Data Engineers, Software Engineers, and Product teams to

productionize ML solutions.

• Implement MLOps practices including model versioning, experiment tracking, CI/CD, monitoring, and automated deployment.

• Review technical designs and code, establish engineering best practices, and mentor other engineers.

Good-to-Have Skills

• Experience with LLMs, NLP, Generative AI, or RAG.

• Experience with PySpark / distributed ML processing.

• Knowledge of Docker, Kubernetes, and microservices.

• Experience with AWS, Azure, or GCP.

• Familiarity with MLflow, Kubeflow, Airflow, or similar ML orchestration tools.

• Experience with real-time inference, model optimization, or distributed systems.

Educational Qualifications

• Bachelor’s or master’s degree in computer science, Engineering, or a related technical field.

• Advanced degree or strong research/open-source contributions in ML is an advantage.