Machine Learning Engineer

2 days ago


New Delhi, India ADP Full time

Total Experience : 8-12years Location : Hyderabad Notice Period : Immediate to 30days only Position : 1We're seeking a talentedML Engineerto help build, deploy, scale and maintain machine learning models and optimize our ML workflows and infrastructure.Key ResponsibilitiesDesign 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 experimentsRequirements 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



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