

AWS Gen AI / ML Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AWS Gen AI / ML Engineer on a contract basis in Plano, TX, offering a competitive pay rate. Requires 3+ years in ML engineering with AWS focus, expertise in AWS services, and strong coding skills in Python, Java, or R.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
June 5, 2025
π - Project duration
Unknown
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ποΈ - Location type
On-site
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Plano, TX
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π§ - Skills detailed
#Automation #Security #Python #Keras #IAM (Identity and Access Management) #"ETL (Extract #Transform #Load)" #Terraform #Cloud #R #API (Application Programming Interface) #TensorFlow #AI (Artificial Intelligence) #TypeScript #GraphQL #PyTorch #REST (Representational State Transfer) #GitHub #Linux #DevOps #Docker #Documentation #Athena #Mathematics #Deep Learning #Computer Science #Migration #JavaScript #SageMaker #Data Engineering #Data Science #VPC (Virtual Private Cloud) #Libraries #Debugging #Statistics #AWS (Amazon Web Services) #Scripting #ML (Machine Learning) #Data Pipeline #Java #Lambda (AWS Lambda) #Data Migration
Role 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
β’ Design and productionize cloud ML pipelines (SageMaker, Step Functions, EKS) that advance predictive-automation roadmap
β’ Integrate foundation models via Bedrock and Anthropic LLM APIs to unlock generative-AI capabilities
β’ Optimize and extend existing ML libraries / frameworks for multi-region, multi-tenant workloads
β’ Partner cross-functionally with data scientists, data engineers, architects, and security teams to deliver end-to-end value
β’ Detect and mitigate data-distribution drift to preserve model accuracy in real-world traffic
β’ Stay current on AWS, MLOps, and generative-AI innovations; drive continuous improvement
Responsibilities
β’ Transform data-science prototypes into secure, highly available AWS services; choose and tune the appropriate algorithms, container images, and instance types
β’ Run automated ML tests/experiments; document metrics, cost, and latency outcomes
β’ Train, retrain, and monitor models with SageMaker Pipelines, Model Registry, and CloudWatch alarms
β’ Build and maintain optimized data pipelines (Glue, Kinesis, Athena, Iceberg) feeding online/offline inference
β’ Collaborate with product managers to refine ML objectives and success criteria; present results to executive stakeholders
β’ Extend or contribute to internal ML libraries, SDKs, and infrastructure-as-code modules (CDK / Terraform)
Skills And Qualifications
β’ Primary technical skills
β’ AWS SDK, SageMaker, Lambda, Step Functions
β’ Machine-learning theory and practice (supervised / deep learning)
β’ DevOps & CI/CD (Docker, GitHub Actions, Terraform/CDK)
β’ Cloud security (IAM, KMS, VPC, GuardDuty)
β’ Networking fundamentals
β’ Java, Springboot, JavaScript/TypeScript & API design (REST, GraphQL)
β’ Linux administration and scripting
β’ Bedrock & Anthropic LLM integration
Secondary / Tool Skills
β’ Advanced debugging and profiling
β’ Hybrid-cloud management strategies
β’ Large-scale data migration
β’ Impeccable analytical and problem-solving ability; strong grasp of probability, statistics, and algorithms
β’ Familiarity with modern ML frameworks (PyTorch, TensorFlow, Keras)
β’ Solid understanding of data structures, modeling, and software architecture
β’ Excellent time-management, organizational, and documentation skills
β’ Growth mindset and passion for continuous learning
Preferred Qualifications
β’ 10+ years of Software Experience
β’ 3+ years in an ML-engineering or cloud-ML role (AWS focus)
β’ Proficient in Python (core), with working knowledge of Java or R
β’ Outstanding communication and collaboration skills; able to explain complex topics to non-technical peers
β’ Proven record of shipping production ML systems or contributing to OSS ML projects
β’ Bachelor's (or higher) in Computer Science, Data Engineering, Mathematics, or a related field
β’ AWS Certified Machine Learning Specialty and/or AWS Solutions Architect Associate a strong plus