AWS Cloud Engineer with Machine Learning Operations

3 weeks ago

Boston, Massachusetts, United States Qualitative Financials Full time

Job Title: AWS Cloud Engineer with Machine Learning Operations

About the Role:

We are seeking a highly skilled AWS Cloud Engineer with expertise in Machine Learning Operations to join our team at Qualitative Financials. As a Cloud Engineer, you will be responsible for building and maintaining large-scale client infrastructure and pipelines, contributing to the development of advanced analytics and machine learning platforms, and extending existing client platforms and frameworks for scaling model training and deployment.

Key Responsibilities:

  • Design and develop feature generation and store frameworks to promote sharing of data and features among different client models.
  • Partner with data scientists to help use the foundational platform upon which models can be built and trained.
  • Build tools to help detect shifts in data and features used by client models to identify issues in advance of deteriorating prediction quality, monitor the uncertainty of model outputs, and automate prediction explanations for model diagnostics.
  • Explore new technology trends and leverage them to simplify our data and client ecosystem.
  • Resolve technical roadblocks and mitigate potential risks.
  • Deliver system automation by setting up continuous integration/continuous delivery pipelines.

Requirements:

  • 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 client ecosystem (numpy, pandas, scikit-learn, TensorFlow, etc.).
  • Experience in building cloud-native applications using AWS services like S3, RDS, CFT, SNS, SQS, Step Functions, Event Bridge, CloudWatch, etc.
  • Experience with building data pipelines in getting the data required to build, deploy, and evaluate client 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.
  • 5+ years of proven experience in implementing big data solutions in data analytics space.
  • Experience in developing client 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.
  • Solid experience in Agile methodologies (Kanban and Scrum).
  • You have strong technical design and analysis skills.
  • 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-structured, and unstructured data.
  • Your experience building client infrastructure, with an eye towards software engineering.

What We Offer:

At Qualitative Financials, we offer a dynamic and challenging work environment, opportunities for professional growth and development, and a competitive compensation package.

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