Data Science AWS Engineer

We are looking for an Data Science

AWS Engineer to join India Data Science team of DolFinTech, USA.

The candidate must have at

least 1 year of direct hands-on

experience in developing, deploying, integrating, and monitoring Machine Learning models and processes on AWS. The candidate must have hands-on experience with

Amazon SageMaker, AWS Lambda, API Gateway, S3, CloudWatch, and AWS-based ETL/data pipelines.

Key Responsibilities

Develop, package, and deploy ML models using

Amazon SageMaker

.

Build and manage

real-time SageMaker inference endpoints

.

Develop

AWS Lambda functions

for model invocation and application integration.

Create and maintain

REST/HTTP APIs using Amazon API Gateway

.

Build and maintain

ETL/data-processing pipelines on AWS

using services such as S3, Glue, Lambda, Athena, and/or Step Functions.

Implement end-to-end ML scoring workflows such as:

Application/API → API Gateway → Lambda → SageMaker → Response

Implement

logging, monitoring, and alerting

using Amazon CloudWatch.

Monitor model/API performance, latency, failures, and production issues.

Troubleshoot AWS deployment, integration, and

IAM/permission issues

.

Support model and code versioning and deployment across

Development, UAT/Staging, and Production

environments.

Work with Data Scientists to convert notebook/prototype models into reliable production solutions.

Mandatory Skills

Minimum 1 year of hands-on AWS and Machine Learning experience

Strong hands-on experience with Amazon SageMaker, AWS Lambda , Amazon API Gateway, Amazon S3, Amazon CloudWatch, AWS IAM, AWS ETL/data-processing pipelines, AWS Glue, Athena

Strong

Python

and

SQL

skills.

Experience deploying ML models into

production environments

.

Experience creating and consuming

REST APIs / JSON interfaces

.

Experience with

Git/version control

.

Good understanding of ML models, feature engineering, model scoring, and model monitoring.

Preferred Skills

Experience with some of the following would be advantageous:

AWS Step Functions / Event Bridge

SageMaker Pipelines / Model Registry / Model Monitor

Docker / Amazon ECR

CI/CD pipelines

Terraform / CloudFormation / AWS CDK

Fraud, credit risk, transaction risk, or financial-services models

Experience & Qualification

1+ years overall experience preferred

Minimum 1 year of direct hands-on AWS experience

Bachelor's/Master's degree in Computer Science, Engineering, Data Science, or a related discipline