What we do:

Uptake is the premier Industrial AI company, providing a predictive analytics SaaS platform that empowers major industry leaders to optimize performance, reduce asset failures, and enhance safety. At Uptake, we combine our strengths — machine learning, analytics, data visualization, and software development — to deliver actionable insights that make industry more reliable, productive, safe and secure.

What Machine Learning Engineers Do Here

Machine Learning is at the core of what we do at Uptake. Machine Learning Engineers are part of the team working to build the core Machine Learning and AI tools that will power Uptake’s future.

Typical day to day tasks for a Machine Learning Engineer might include:

  • Building and maintaining software libraries used by data scientists to quickly build, evaluate, and deploy machine learning models into production.
  • Evangelizing software engineering best practices across data science teams at Uptake and encouraging best practices by building them into our libraries and tools where possible.
  • Translating customer needs into technical requirements for machine learning model deployment.
  • Collaborating with Data Science, Product, and Engineering stakeholders to define and implement new services to accelerate the ML model deployment lifecycle and other data science tasks.
  • Keeping up to date with new ML concepts and technologies to keep our libraries and tools on the cutting edge of the discipline.
  • Collaborating with the engineering team that maintains our data science platform to improve the entire ML ecosystem at Uptake.

What We Are Looking For

  • Bachelor's degree or higher in a relevant field
  • Passion for machine learning! We want candidates who love machine learning and are excited about what they do.
    • Some ways previous successful candidates have demonstrated this are by:
      • Writing relevant blog posts and/or articles.
      • Participating in relevant online communities.
      • Participating in Kaggle competitions.
      • Sharing details about personal or professional projects in the machine learning space within a cover letter.
      • Receiving recognition via professional or academic awards (example: Most Valuable Employee, scholastic grants).
      • Expressing detailed knowledge of and genuine interest in Uptake’s unique methods, products, data, and technology within a cover letter.
  • Ability to write production-level machine learning code in Python; or Java, Scala, or similar JVM-based languages.
    • Some ways previous successful candidates have demonstrated this are by:
      • Contributing to influential Open Source Projects like Docker, Kafka, Spark, Kubernetes, sklearn, XGBoost, Tensorflow, pytorch, Elasticsearch etc.
      • Describing a machine learning project they developed that is deployed in a live setting within a resume or cover letter.
      • Making a high quality machine learning project available in a public forum like GitHub or Kaggle.
      • Publishing work in machine learning related journals or conferences.
  • Familiarity with data science workflows, and concepts like exploratory data analysis, training, and scoring

Nice to Have

  • 2+ years of applied software engineering experience, data science experience, or a combination of the two
  • Experience writing production code in Python as well as Java, Scala, or similar JVM based languages
  • Experience developing and maintaining software packages (particularly Python) 
  • Experience with container technology (like Docker) and container orchestration (like Kubernetes)
  • Experience with stream processing with tools like Kafka or Flink
  • Experience working with web based APIs
  • Experience working on concepts like AutoML or end-to-end learning
  • Experience deploying and maintaining Machine Learning models into production
  • Experience with CI/CD tools like Jenkins
  • Substantive contributions to open source projects in the areas of data science or machine learning

Applicants must be authorized to work in the U.S.

Uptake welcomes and encourages applications from all individuals, without regard to any prohibited ground of discrimination, including from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process.

 

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