MLOps Engineer - Remote (AWS Certified Machine Learning) (San Diego) Job at MillenniumSoft Inc, San Diego, CA

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  • MillenniumSoft Inc
  • San Diego, CA

Job Description

Overview

Join to apply for the MLOps Engineer - Remote (AWS Certified Machine Learning) role at MillenniumSoft Inc .

Location : San Diego, CA

Duration : 10+ Months

Total Hours/week : 40

1st Shift

Client : Medical Devices Company

Level of Experience : Senior Level

Employment Type : Contract on W2 (Need US Citizens or GC Holders or GC EAD or OPT or EAD or CPT)

Responsibilities

  • We\'re seeking an experienced MLOps Engineer to lead the operationalization of our Machine Learning workloads.
  • As a key team member, you\'ll be responsible for designing, building, and maintaining infrastructure required for efficient development, deployment, and monitoring of machine learning workloads.
  • Your close collaboration with data scientists will ensure that our models are reliable, scalable, and performing optimally.
  • This role requires expertise in automating ML workflows, enhancing model reproducibility, and ensuring continuous integration and delivery.

Qualifications

  • Bachelor\'s or Master\'s degree in Computer Science, Engineering, or a related field.
  • 3+ years of experience in MLOps, DevOps, or related fields.
  • Strong programming skills in Python, GoLang with experience in other languages such as Java, C++, or Scala being a plus.
  • Experience with ML frameworks such as TensorFlow, PyTorch, and/or scikit-learn.
  • Proficiency with CI/CD tools such as Github Actions.
  • Hands-on experience with AWS.
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Knowledge of infrastructure-as-code tools such as AWS CDK and Cloudformation.
  • Strong understanding of machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
  • Excellent problem-solving skills and the ability to work independently as well as part of a team.
  • Strong communication skills and the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications

  • AWS Certified Machine Learning - Specialty
  • Experience with feature stores, model registries, and monitoring tools such as MLflow, Tecton, or Seldon.
  • Familiarity with data engineering tools such as AWS EMR, Glue and Apache Spark.
  • Knowledge of security best practices for machine learning systems.
  • Experience with A/B testing and model performance monitoring.

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Job Tags

Full time, Contract work, Remote work, Day shift,

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