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Urgent! Machine Learning +Aws+ (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) +Sagemaker Job Opening In Panchkula – Now Hiring DigiHelic Solutions Pvt. Ltd.

Machine Learning +Aws+ (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) +Sagemaker



Job description

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


Required Skill Profession

Computer Occupations



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