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Recurring Decimal Linkedin · Posted 2d ago

Machine Learning Engineer

Allen, Texas, United States

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Indexed description

We're seeking a Senior Software Engineer for our Product Development team, building large-scale, cloud-based big data and MLOps platforms and APIs that integrate diverse data sources across a leading data and analytics organization's products and delivery channels.

Requirements:

  • BS in Computer Science or related field; MS preferred
  • 7-8 years' experience in engineering roles (software engineer, technical lead)
  • 3-4+ years' AWS experience architecting scalable, secure, cost-effective cloud-native solutions
  • Agile/scrum experience
  • Knowledge of AWS Well-Architected Framework and cloud best practices
  • MLOps platform experience (SageMaker, Kubeflow, or MLflow)- MANDATORY
  • Python development experience (Flask, Django, AsyncIO)-MANDATORY
  • Distributed systems experience: integration, testing, troubleshooting, monitoring, error recovery
  • API, real-time systems, and microservices design experience
  • AWS services experience (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate)
  • CI/CD tools familiarity (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness)
  • Async messaging/queue experience (Kafka, RabbitMQ, SQS)
  • Strong problem-solving, analytical, and communication skills
  • Effective in fast-paced, globally distributed team environments

Responsibilities:

  • Design scalable, resilient cloud architectures with Architecture/Product/CloudOps/Engineering teams using AWS best practices
  • Build ML pipelines using Python, AWS (SageMaker, Lambda, Step Functions, S3, ECR), and containers (Docker, ECS/Fargate)
  • Contribute to design reviews and technical documentation
  • Ensure code quality through testing and code reviews
  • Communicate technical decisions to product and delivery teams
  • Drive quality/efficiency improvements via defect prevention and root cause analysis
  • Prototype new technology integrations
  • Support business requirement analysis with product teams
  • Tune performance of existing and new systems


Nice to have: Dynatrace/Splunk, TensorFlow/PyTorch/scikit-learn, Kubeflow/MLflow/Airflow, automated analytical pipelines

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