Machine Learning +Aws+

4 days ago

India DigiHelic Solutions Pvt. Ltd. Full time

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 efficiency ● Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks. ● Data Preparation: Prepare, cleanse, and transform data for model training and evaluation. ● Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models. ● System Integration: Integrate models into existing systems and workflows. ● Model Deployment: Deploy models to production environments and monitor performance. ● Collaboration: Work closely with data scientists, software engineers, and other stakeholders. ● Continuous Improvement: Identify areas for improvement in model performance and systems. Skills: ● 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 evaluation. Required 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

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