Total Experience : 8-12years

Location : Hyderabad

Notice Period : Immediate to 30days only

Position : 1

We're seeking a talented ML Engineer to help build, deploy, scale and maintain machine learning models and optimize our ML workflows and infrastructure.

Key Responsibilities

• Design and develop high-performance, scalable, and reliable machine learning pipelines and model deployment systems
• Build and maintain MLOps infrastructure for model training, validation, deployment, and monitoring
• Create automated ML workflows for data preprocessing, feature engineering, model training, and evaluation
• Deploy models to production environments and ensure optimal performance and reliability
• Integrate ML models with existing data infrastructure and APIs
• Implement model versioning, A/B testing frameworks, and continuous integration/deployment for ML systems
• Monitor model performance, detect drift, and implement retraining strategies
• Create custom tools and frameworks to streamline ML development and deployment processes
• Collaborate with data scientists to productionize research models and experiments

Requirements

• Proficiency in machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or MLflow
• Strong expertise in Python and/or Scala for ML development. Experience with R is a plus
• Excellent knowledge of ML algorithms, statistical methods, and model evaluation techniques
• Deep understanding of MLOps practices, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure)
• Proficiency in distributed computing and experience with Spark for large-scale ML workloads
• Experience with model serving frameworks (TensorFlow Serving, Seldon, KubeFlow) and API development
• Knowledge of feature stores, experiment tracking, and ML metadata management
• Experience with SQL/NoSQL databases and data warehousing for ML feature engineering
• Understanding of software engineering best practices, version control (Git), and CI/CD pipelines
• Experience with monitoring and observability tools for ML systems
• Ability to work independently and collaboratively within cross-functional teams
• Flexible, adaptive, quick learner with strong problem-solving skills