Machine Learning Engineer - AWS Platform

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.