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Kinetica // GPU-accelerated, in-memory analytics database
 
Engineering, Full Time       Posted: Thursday, February 13, 2020
 
   
 
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Company Description

The Kinetica Active Analytics Platform combines streaming & historical data with location intelligence & machine learning-powered analytics. Organizations across automotive, energy, telecommunications, retail, healthcare, financial services, & beyond leverage the platform's GPU-accelerated computing power to build custom analytical applications that deliver immediate, dynamic insight. Kinetica has a rich partner ecosystem, including NVIDIA, Dell, HP, & IBM, & is privately held, backed by leading global venture capital firms Canvas Ventures, Citi Ventures, GreatPoint Ventures, & Meritech Capital Partners.

For more information & trial downloads, visit kinetica.com or follow us on LinkedIn & Twitter.

Job Description

Kinetica seeks a Senior Software Engineer with Python & Distributed Systems experience. As a member of the ML Product Engineering Team, you'llbuild out the product in Python & integrate all other parts (Kubernetes, Docker, & our GPU-powered DB, etc) using Python bindings to build & deliver an overall product (a REST API.) This is a Product Engineering role, so we are building a generic solution that works across many industries, many use-cases, many clients, many data varieties, many data volumes, & many data velocities (rather than building for a specific use case or a specific client -- this offers a huge opportunity to make a mark on a fast-growing industry.)

Job Responsibilities

  • Integrate a variety of components into an overall smooth-functioning product
  • Ability to bring things to a close -- not just exploring but getting things to the finish line.
  • Research products & keep abreast of marketplace offerings & possibilities
  • Work with commercial & open-source packages to find stacks to achieve required product features
  • Work with a close-knit team to design & develop a release-quality commercial product
  • Work with our broader engineering group to ensure products fit into the company's product lineup
  • Work iteratively to hone proofs-of-concept for new product features & steadily merge development into the overall product
  • Keep attuned to the marketplace & spot opportunities to expand functionality in response to new technical capabilities as they arise
  • Keep attuned to customer use & actively work to improve product experience to meet usage, both current & future usage the customer may not even realize they need

Qualifications
  • Technical Degree in Computer Science, Operations Research, Statistics, Math, Physics, or equivalent
  • 5+ years of Python development experience
  • Proficiency working in Linux development environments
  • Experience in structured work environments with automated-testing & quality processes
  • Experience developing REST APIs
  • Familiarity with SQL & databases
  • Familiarity with containerized Python applications (Docker specifically)
  • Desire to work with large datasets
  • Exposure to one machine learning open-source package (sklearn, TensorFlow, Caffe2, Torch, etc.)
  • Strong communication skills, written & verbal, used in a fast-moving environment

Bonus Qualifications:

  • Familiarity with Container Orchestration (Kubernetes specifically)
  • Strong communication skills as demonstrated by personal projects, technical blog postings, volunteer activities, etc.
  • Interest in Machine Learning & Data Science
  • Experience working with highly complex technical ecosystems (resource managers, containers, automated testing -- e.g., Mesos, Kubernetes, Docker)
  • Familiarity with popular python libraries (NumPy)
  • Understanding of the data science ecosystem -- commercial & open source
  • Participation in hackathons; wins at hackathons or Kaggle leaderboards are even more impressive
  • Experience working with computational systems (e.g., NumPy, Pandas, Spark, etc.)

Applicants are encouraged to share online project/code portfolios & any demonstrations of community participation (e.g., public Github profiles, public StackOverflow profiles, public Kaggle profiles, technical blog postings, etc.)

Additional Information

All your information will be kept confidential according to EEO guidelines.

 
 
 
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