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Urgent! AWS ML Cloud Engineer Job Opening In Plano Texas – Now Hiring Tek Spikes



Job description

Responsibilities:


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


Required Skill Profession

Architecture And Engineering



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