AWS Gen AI / ML Engineer

  • Plano, TX
  • Posted 1 day ago | Updated 1 day ago

Overview

On Site
$65+
Contract - W2
Contract - 12 Month(s)

Skills

API
Algorithms
Amazon Kinesis
Amazon SageMaker
Amazon Web Services
Artificial Intelligence
Continuous Integration
Cloud Computing
Communication
Computer Science
Continuous Delivery
Data Engineering
Data Migration
Data Science
Deep Learning
DevOps
Distribution
Docker
Fluency
Generative Artificial Intelligence (AI)
GitHub
GraphQL
Java
JavaScript
Keras
Linux
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
TensorFlow
Spring Framework

Job Details

AWS Gen AI / ML Engineer

Location: Plano, TX (Onsite 5 days/week)
Job Type: Contract

< data-start="342" data-end="369">Position Summary</>

We're seeking a hands-on AWS ML Cloud Engineer to design, deploy, and optimize cloud-native machine learning systems. You'll help power our next-generation predictive automation platform, integrating generative AI capabilities via AWS Bedrock and Anthropic APIs. Ideal candidates combine ML expertise, AWS fluency, and DevOps discipline to ship secure, scalable, and cost-effective solutions.

Objectives

  • Design and productionize ML pipelines using SageMaker, Step Functions, and EKS

  • Integrate foundation models via AWS Bedrock and Anthropic APIs

  • Optimize existing ML frameworks for multi-region, multi-tenant workloads

  • Collaborate cross-functionally with Data Science, Engineering, Architecture, and Security teams

  • Monitor and mitigate data distribution drift to maintain model performance

  • Stay ahead of AWS, MLOps, and Gen AI advancements to drive platform evolution

Key Responsibilities

  • Transform ML prototypes into secure, highly available AWS services

  • Conduct automated ML tests, experiments, and document performance (latency, cost, metrics)

  • Train, deploy, and monitor models using SageMaker Pipelines, Model Registry, and CloudWatch

  • Maintain optimized data pipelines via AWS Glue, Kinesis, Athena, Iceberg

  • Collaborate with product stakeholders to define success criteria and report outcomes

  • Contribute to internal ML libraries, SDKs, and IaC modules (Terraform / CDK)

Required Skills

Core Technical

  • AWS: SageMaker, Lambda, Step Functions, IAM, KMS, VPC, GuardDuty

  • ML theory and practical applications (supervised & deep learning)

  • CI/CD, DevOps: Docker, GitHub Actions, Terraform/CDK

  • Programming: Python, Java, Spring Boot, JavaScript/TypeScript

  • Networking & Linux fundamentals

  • REST/GraphQL API design

  • Gen AI: AWS Bedrock, Anthropic APIs

Secondary / Tools

  • Debugging/profiling large-scale systems

  • Hybrid-cloud & data migration strategies

  • PyTorch, TensorFlow, Keras familiarity

  • Advanced statistics and algorithm knowledge

  • Excellent time management and documentation

  • Strong communication skills and collaborative mindset

Preferred Qualifications

  • 12+ years in Software Engineering

  • 5+ years in ML Engineering / Cloud ML roles (preferably AWS)

  • Proficient in Python; working knowledge of Java or R

  • Experience deploying production ML systems

  • Contributions to open-source ML projects a plus

  • Bachelor's or higher in Computer Science, Data Engineering, Mathematics, or related field

  • AWS ML Specialty and/or Solutions Architect Associate certification preferred

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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