Ml Engineer
- UST Global Solutions
- 4 - 8 years
- India
- 18 hours ago
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Job Description
Key Responsibilities:
- Cloud-Based Development: Design, develop, and deploy scalable solutions using AWS services such as S3, Kinesis, Lambda, Redshift, DynamoDB, Glue, and SageMaker.
- Data Processing & Pipelines: Implement efficient data pipelines and optimize data processing using pandas, Spark, and PySpark.
- Machine Learning Operations (MLOps): Work with model training, model registry, model deployment, and monitoring using AWS SageMaker and related services.
- Infrastructure-as-Code (IaC): Develop and manage AWS infrastructure using AWS CDK and CloudFormation to enable automated deployments.
- CI/CD Automation: Set up and maintain CI/CD pipelines using GitHub, AWS CodePipeline, and CodeBuild for streamlined development workflows.
- Logging & Monitoring: Implement robust monitoring and logging solutions using Splunk, DataDog, and AWS CloudWatch to ensure system performance and reliability.
- Code Optimization & Best Practices: Write high-quality, scalable, and maintainable Python code while adhering to software engineering best practices.
- Collaboration & Mentorship: Work closely with cross-functional teams, providing technical guidance and mentorship to junior developers.Role & responsibilities
Qualifications & Requirements:
- 7+ years of experience in software development with a strong focus on Python.
- Expertise in AWS services, including S3, Kinesis, Lambda, Redshift, DynamoDB, Glue, and SageMaker.
- Proficiency in Infrastructure-as-Code (IaC) tools like AWS CDK and CloudFormation.
- Experience with data processing frameworks such as pandas, Spark, and PySpark.
- Understanding of machine learning concepts, including model training, deployment, and monitoring.
- Hands-on experience with CI/CD tools such as GitHub, CodePipeline, and CodeBuild.
- Proficiency in monitoring and logging tools like Splunk and DataDog.
- Strong problem-solving skills, analytical thinking, and the ability to work in a fast-paced, collaborative environment.
Preferred Skills & Certifications:
- AWS Certifications (e.g., AWS Certified Solutions Architect, AWS Certified DevOps Engineer, AWS Certified Machine Learning).
- Experience with containerization (Docker, Kubernetes) and serverless architectures.
- Familiarity with big data technologies such as Apache Kafka, Hadoop, or AWS EMR.
- Strong understanding of distributed computing and scalable architectures.
Skills
Python,MLOps, AWS
NOTE : Above 1 month official notice period candidates please don't apply.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: UST Global SolutionsLocation(s): india+ View Contact
Keyskills: CI CD Pipeline MLOps AWS - sagemaker Python Artificial Intelligence Machine Learning
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