Find The RightJob.
AI/ML Engineer
Must Have Technical/Functional Skills
Technical Skills
- 4–8+ years in ML engineering with production deployments.
- Strong Python expertise (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
- Hands-on with Amazon SageMaker Pipelines & Feature Store.
- Experience building containerized ML solutions (Docker).
- Knowledge of API deployment (REST/gRPC).
- SQL expertise for insurance data modeling.
AWS Expertise
- Deep experience in:
- SageMaker model training & deployment
- IAM policies & VPC configurations
- S3 lifecycle policies
- Infrastructure as Code (CloudFormation / Terraform)
Roles & Responsibilities
Key Responsibilities
ML Model Development – Insurance Use Cases
- Build predictive models for:
- Claims severity & frequency prediction
- Fraud detection (SIU support models)
- Underwriting risk scoring
- Loss ratio forecasting
- Policy lapse prediction
- Implement NLP models for claims notes, adjuster reports, and policy documents.
- Develop computer vision models for damage assessment (auto/property insurance).
MLOps & Production Deployment
- Design end-to-end ML pipelines using:
- Amazon SageMaker (training, pipelines, endpoints, feature store)
- AWS Lambda
- Amazon S3
- Amazon ECR
- Amazon ECS / Amazon EKS
- Implement CI/CD for ML using:
- AWS CodePipeline
- AWS CodeBuild
- Manage model versioning, retraining workflows, and rollback strategies.
- Deploy real-time and batch inference endpoints.
- Implement model monitoring (data drift, concept drift, bias detection).
Security, Risk & Compliance
- Implement secure ML architecture aligned to insurance regulatory requirements.
- Encrypt data at rest and in transit.
- Document model governance and validation processes for actuarial and compliance review.
Required Qualifications
Technical Skills
- 4–8+ years in ML engineering with production deployments.
- Strong Python expertise (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow).
- Hands-on with Amazon SageMaker Pipelines & Feature Store.
- Experience building containerized ML solutions (Docker).
- Knowledge of API deployment (REST/gRPC).
- SQL expertise for insurance data modeling.
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 & H olidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
Salary Range: $120,000 - $140,000 a year
Location
New York, NY
Job Function
TECHNOLOGY
Role
Senior Engineer
Job Id
402530
Desired Skills
AWS | Machine Learning
Salary Range
$120,000-$140,000 a year
Desired Candidate Profile
Qualifications : BACHELOR OF COMPUTER SCIENCE
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