AWS Gen AI / ML Engineer

Jobs via Dice; Plano (TX); On-site; USD 110,000 - 130,000; Full time

Job summary

A leading company in the software industry seeks an AWS Gen AI / ML Engineer to enhance its predictive-automation platform. This role focuses on designing and deploying machine-learning systems using AWS technologies. The ideal candidate will possess deep ML expertise and experience in cloud environments to ensure high-impact insights and efficient solutions.

Qualifications

• 10+ years of software experience required.
• 3+ years in an ML-engineering or cloud-ML role with AWS focus.
• Proficiency in Python and knowledge of Java or R preferred.

Responsibilities

• Design and optimize cloud ML pipelines and AWS services.
• Run automated ML tests and document outcomes.
• Collaborate with teams to refine ML objectives.

Skills

AWS SDK

SageMaker

Machine-learning theory and practice

DevOps & CI/CD

Cloud security

Networking fundamentals

Java

Linux administration

Data analysis

Education

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

Tools

Terraform/CDK

PyTorch

TensorFlow

Job description

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Dice is the leading career destination for tech experts at every stage of their careers. Our client, Nava Software Solutions, is seeking the following. Apply via Dice today!

NAVA Software solutions is looking for an AWS Gen AI / ML Engineer

Details:

AWS Gen AI / ML Engineer

Location: Plano, TX - Onsite 5 days

Job Type: Contract

Description: We are seeking an AWS ML Cloud Engineer to design, deploy, and optimize cloud-native machine-learning systems that power our next-generation predictive-automation platform. You will blend deep ML expertise with hands-on AWS engineering, turningdata into low-latency, high-impact insights. The ideal candidate commands statistics, coding, and DevOps-and thrives on shipping secure, cost-efficient solutions at scale

Objectives of this role

• Design and productionize cloud ML pipelines (SageMaker, Step Functions, EKS) that advance predictive-automation roadmap
• Integrate foundation models via Bedrock and Anthropic LLM APIs to unlock generative-AI capabilities
• Optimize and extend existing ML libraries / frameworks for multi-region, multi-tenant workloads
• Partner cross-functionally with data scientists, data engineers, architects, and security teams to deliver end-to-end value
• Detect and mitigate data-distribution drift to preserve model accuracy in real-world traffic
• Stay current on AWS, MLOps, and generative-AI innovations; drive continuous improvement
  
  

Responsibilities

• Transform data-science prototypes into secure, highly available AWS services; choose and tune the appropriate algorithms, container images, and instance types
• Run automated ML tests/experiments; document metrics, cost, and latency outcomes
• Train, retrain, and monitor models with SageMaker Pipelines, Model Registry, and CloudWatch alarms
• Build and maintain optimized data pipelines (Glue, Kinesis, Athena, Iceberg) feeding online/offline inference
• Collaborate with product managers to refine ML objectives and success criteria; present results to executive stakeholders
• Extend or contribute to internal ML libraries, SDKs, and infrastructure-as-code modules (CDK / Terraform)
  
  

Skills And Qualifications

• Primary technical skills
• AWS SDK, SageMaker, Lambda, Step Functions
• Machine-learning theory and practice (supervised / deep learning)
• DevOps & CI/CD (Docker, GitHub Actions, Terraform/CDK)
• Cloud security (IAM, KMS, VPC, GuardDuty)
• Networking fundamentals
• Java, Springboot, JavaScript/TypeScript & API design (REST, GraphQL)
• Linux administration and scripting
• Bedrock & Anthropic LLM integration
  
  

Secondary / Tool Skills

• Advanced debugging and profiling
• Hybrid-cloud management strategies
• Large-scale data migration
• Impeccable analytical and problem-solving ability; strong grasp of probability, statistics, and algorithms
• Familiarity with modern ML frameworks (PyTorch, TensorFlow, Keras)
• Solid understanding of data structures, modeling, and software architecture
• Excellent time-management, organizational, and documentation skills
• Growth mindset and passion for continuous learning
  
  

Preferred Qualifications

• 10+ years of Software Experience
• 3+ years in an ML-engineering or cloud-ML role (AWS focus)
• Proficient in Python (core), with working knowledge of Java or R
• Outstanding communication and collaboration skills; able to explain complex topics to non-technical peers
• Proven record of shipping production ML systems or contributing to OSS ML projects
• Bachelor's (or higher) in Computer Science, Data Engineering, Mathematics, or a related field
• AWS Certified Machine Learning Specialty and/or AWS Solutions Architect Associate a strong plus

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development

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