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 todeep learning along with employing LLMs in modern frameworks.
Data Preparation : Prepare, cleanse, and transform data for model training andevaluation.
Algorithm Implementation : Implement and optimize machine learning algorithms andstatistical models.
System Integration : Integrate models into existing systems and workflows.Model Deployment : Deploy models to production environments and monitorperformance.
Collaboration : Work closely with data scientists, software engineers, and otherstakeholders.
Continuous Improvement : Identify areas for improvement in model performance andsystems.
Skills :
Programming and Software Engineering : Knowledge of software engineering bestpractices (version control, testing, CI / CD).
Data Engineering : Ability to handle data pipelines, data cleaning, and featureengineering. 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 toproduction 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 inML workflows
AWS data : Redshift, GlueContainerization and Orchestration : Understanding of Docker and Kubernetes, and theirimplementation within AWS (EKS, ECS)
Skills :
Aws, Aws Cloud, Amazon Redshift, Eks