ML Engineer

Tata Consultancy Services; Malvern (Chester County); On-site; USD 100,000 - 135,000; Full time

Benefits offered by this job

Discretionary Annual Incentive

Comprehensive Medical Coverage

Maternal & Parental Leaves

401K Plan

Certification & Training Reimbursement

Vacation & Holidays

Job summary

Tata Consultancy Services is seeking a seasoned ML Engineer to design, build, and deploy scalable machine learning solutions on AWS. You will own end-to-end pipelines, coordinate with data scientists and engineers, and ensure robust deployment, monitoring and governance of models.

Ideal candidates will have hands-on experience with SageMaker, Scikit-learn, TensorFlow/PyTorch, and a strong background in data engineering using AWS services.

Qualifications

• Bachelor's degree in Computer Science or related field.

Responsibilities

• Design, build, and deploy scalable Machine Learning solutions on AWS using SageMaker, ensuring high performance, reliability, and security.
• Develop and maintain end-to-end ML pipelines, including data preparation, model training, hyperparameter tuning, deployment, and monitoring.
• Collaborate with data scientists, engineers, and business stakeholders to operationalize ML models, automate workflows, and drive business outcomes through AI/ML solutions.

Skills

Leadership

Stakeholder communication

Cloud architecture

End-to-end ML design

Education

Bachelor of Computer Science

Tools

SageMaker

Scikit-learn

XGBoost

TensorFlow

PyTorch

S3

EC2

IAM

Lambda

ECR

ECS/EKS

CloudWatch

Step Functions

AWS Glue

Athena

Redshift

EMR

Pandas

NumPy

Boto3

Job description

• Amazon SageMaker Expertise - Strong experience with SageMaker Studio, Training Jobs, Pipelines, Model Registry, Feature Store, and Endpoint Deployment.
• Machine Learning & Deep Learning - Hands-on experience building, training, tuning, and deploying ML/DL models using Scikit-learn, XGBoost, TensorFlow, and PyTorch.
• AWS Cloud Services - Proficiency in S3, EC2, IAM, Lambda, ECR, ECS/EKS, CloudWatch, and Step Functions for ML workloads.
• MLOps & CI/CD - Experience implementing automated ML pipelines, model versioning, deployment automation, monitoring, and retraining workflows.
• Python Programming - Strong coding skills with Python and ML libraries such as Pandas, NumPy, Scikit-learn, and Boto3.
• Data Engineering & Analytics - Experience with data ingestion, transformation, and processing using AWS Glue, Athena, Redshift, and EMR.
• Model Monitoring & Governance - Expertise in data drift detection, model performance monitoring, explainability, and governance using SageMaker monitoring capabilities.
• Solution Architecture & Leadership - Ability to design scalable end-to-end ML solutions on AWS, lead technical discussions, mentor teams, and collaborate with business stakeholders.

Job Description

Must Have Technical/Functional Skills

• Amazon SageMaker Expertise - Strong experience with SageMaker Studio, Training Jobs, Pipelines, Model Registry, Feature Store, and Endpoint Deployment.
• Machine Learning & Deep Learning - Hands-on experience building, training, tuning, and deploying ML/DL models using Scikit-learn, XGBoost, TensorFlow, and PyTorch.
• AWS Cloud Services - Proficiency in S3, EC2, IAM, Lambda, ECR, ECS/EKS, CloudWatch, and Step Functions for ML workloads.
• MLOps & CI/CD - Experience implementing automated ML pipelines, model versioning, deployment automation, monitoring, and retraining workflows.
• Python Programming - Strong coding skills with Python and ML libraries such as Pandas, NumPy, Scikit-learn, and Boto3.
• Data Engineering & Analytics - Experience with data ingestion, transformation, and processing using AWS Glue, Athena, Redshift, and EMR.
• Model Monitoring & Governance - Expertise in data drift detection, model performance monitoring, explainability, and governance using SageMaker monitoring capabilities.
• Solution Architecture & Leadership - Ability to design scalable end-to-end ML solutions on AWS, lead technical discussions, mentor teams, and collaborate with business stakeholders.

Roles & Responsibilities

• Design, build, and deploy scalable Machine Learning solutions on AWS using SageMaker, ensuring high performance, reliability, and security.
• Develop and maintain end-to-end ML pipelines, including data preparation, model training, hyperparameter tuning, deployment, and monitoring.
• Collaborate with data scientists, engineers, and business stakeholders to operationalize ML models, automate workflows, and drive business outcomes through AI/ML solutions.

Generic Managerial Skills, If any

• Strong leadership and stakeholder management skills, with experience leading cross-functional teams and driving delivery excellence.
• Proven effective communication with business and technical stakeholders.

TCS Employee Benefits Summary

Discretionary Annual Incentive.

Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support: Maternal & Parental Leaves.

Insurance Options: Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.

Time Off: Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Salary Range: $100,000 - 135,000 a year

Qualifications

BACHELOR OF COMPUTER SCIENCE