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ML Engineer II - Aws, Aws Cloud
Global Digital Transformation Solutions Provider
ML Engineer II - Aws, Aws Cloud
Peak Hire Solutions's logo

ML Engineer II - Aws, Aws Cloud

at Global Digital Transformation Solutions Provider

Agency job
6 - 12 yrs
₹10L - ₹30L / yr
Pune
Skills
skill iconAmazon Web Services (AWS)
AWS CloudFormation
Amazon Redshift
skill iconElastic Search
ECS
skill iconDocker
skill iconKubernetes
skill iconMachine Learning (ML)
MLOps
Neo4J
SQL
Algorithms
Architecture
Statistical Modeling
Large Language Models (LLM)
skill iconDeep Learning

Job Details

Job Title: ML Engineer II - Aws, Aws Cloud

Industry: Technology

Domain - Information technology (IT)

Experience Required: 6-12 years

Employment Type: Full Time

Job Location: Pune

CTC Range: Best in Industry


Job Description:

Core Responsibilities:

? 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


Must-Haves

Aws, Aws Cloud, Amazon Redshift, Eks

NP: Immediate – 30 Days

 

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Full Stack Developer - Averlon
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