Job Role : ML Engineer.
Experience : 6-12 Years.
Location : Pune, Bangalore, Hyderabad, Trivandrum, Chennai, Kochi, Gurgaon, Noida.
Key Summary :
The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and Development :
- Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern Preparation :
- Prepare, cleanse, and transform data for model training and Implementation :
- Implement and optimize machine learning algorithms and statistical Integration :
- Integrate models into existing systems and Deployment :
Deploy models to production environments and monitor :
Work closely with data scientists, software engineers, and other Improvement :Identify areas for improvement in model performance and :Programming and Software Engineering : Knowledge of software engineering best practices (version control, testing, CI / CD).Data Engineering : Ability to handle data pipelines, data cleaning, and feature engineering.Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch, Neo4J graph.Model Deployment and Monitoring : MLOps Experience in deploying ML models to production environments.Knowledge of model monitoring and performance experience :Amazon SageMaker : Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sagemaker pipeline with ability to analyze gaps and recommend / implement improvements.AWS Cloud Infrastructure : Familiarity with S3, EC2, Lambda and using these services in ML workflows.AWS data : Redshift, Glue.Containerization and Orchestration : Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS).Skills :
Aws, Aws Cloud, Amazon Redshift, Eks.(ref : hirist.tech)