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AI/ML Ops Engineer with AWS experience
AI/ML Ops Engineer with AWS experienceCompunnel Inc. • Durham, North Carolina, United States
AI / ML Ops Engineer with AWS experience

AI / ML Ops Engineer with AWS experience

Compunnel Inc. • Durham, North Carolina, United States
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Job Title : AI / ML Ops Engineer with AWS experience - W2 Only - We can provide sponsorship as well

Duration : Long Term

Location : Durham, NC / Westlake, TX - Hybrid

Must Have :

  • Deep SageMaker MLOps platform design
  • Experience building feature stores
  • Strong Step Functions / EventBridge automation
  • AWS experience
  • Python Experience

The Expertise You Have

  • Has Bachelor’s or Master’s Degree in a technology related field (e.g. Engineering, Computer Science, etc.).
  • Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.).
  • Experience in building cloud native applications using AWS services like S3, RDS, CFT, SNS, SQS, Step functions, Event Bridge, cloud watch etc.,
  • Experience with building data pipelines in getting the data required to build, deploy and evaluate ML models, using tools like Apache Spark, AWS Glue or other distributed data processing frameworks.
  • Data movement technologies (ETL / ELT), Messaging / Streaming Technologies (AWS SQS, Kinesis / Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies.
  • Strong knowledge of developing highly scalable distributed systems using Open-source technologies.
  • 5+ years of proven experience in implementing Big data solutions in data analytics space.
  • Experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker.
  • Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.
  • Experience with CI / CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration / DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).
  • Solid experience in Agile methodologies (Kanban and SCRUM).

    • The Skills You Bring

  • You have strong technical design and analysis skills.
  • You the ability to deal with ambiguity and work in fast paced environment.
  • Your experience supporting critical applications.
  • You are familiar with applied data science methods, feature engineering and machine learning algorithms.
  • Your Data wrangling experience with structured, semi-structure and unstructured data.
  • Your experience building ML infrastructure, with an eye towards software engineering.
  • You have excellent communication skills, both through written and verbal channels.
  • You have excellent collaboration skills to work with multiple teams in the organization.
  • Your ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem.

    • The Value You Deliver

  • Designing & developing a feature generation & store framework that promotes sharing of data / features among different ML models.
  • Partner with Data Scientists and to help use the foundational platform upon which models can be built and trained.
  • Operationalize ML Models at scale (e.g. Serve predictions on tens of millions of customers).
  • Build tools to help detect shifts in data / features used by ML models to help identify issues in advance of deteriorating prediction quality, monitoring the uncertainty of model outputs, automating prediction explanation for model diagnostics.
  • Exploring new technology trends and leveraging them to simplify our data and ML ecosystem.
  • Driving Innovation and implementing solutions with future thinking.
  • Guiding teams to improve development agility and productivity.
  • Resolving technical roadblocks and mitigating potential risks.
  • Delivering system automation by setting up continuous integration / continuous delivery pipelines.
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    Engineer Aws • Durham, North Carolina, United States

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