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Senior Machine Learning Job In Bombora At Nevada

Senior Machine Learning Engineer

  • Full-Time
  • Nevada
  • Bombora
  • Posted 3 years ago – Accepting applications
Job Description
Sr. Machine Learning Engineer (Remote, US)

(Reno, NV / New York, NY / Remote)

Bombora provides a global B2B intent platform powered by the world's largest publisher data co-op. Our data allows sales teams to base their actions on the knowledge of which companies are in-market for their products and empowers marketing teams to practice #SustainableMarketing. We process billions of content interactions daily to detect intent signals from companies around the world.

Bombora is growing and we need you to help us succeed!

Bombora Data Science team is tasked with knowledge extraction and insight generation from Bombora's significant reserves of consumer intent data. We are passionate about understanding the complex systems we model and extracting real value from the massive data we analyze. A significant undertaking, we enjoy the challenge, and have fun with the entire Bombora team doing so.

You will join the Data Science (DS) team, assisting our ambitious and mission-critical task to build models to detect intent signals from companies all across the world. You will contribute to Bombora's machine learning model lifecycle competencies, across model artifact generation, deployment and monitoring. You will design and implement validation and performance reporting workflows for our production models. You will have fun (or we really hope you do).

You will.
  • Design and develop tooling and pipelines to streamline the training, delivery, management and monitoring of models in our production system.
  • Design robust performance metrics and reporting for continuous validation of models across multiple use cases.
  • Implement models, algorithms and machine learning operations, leveraging Apache Spark, PyTorch, Scikit Learn and other ML libraries.
  • Employ test-driven development, performance benchmarking, rapid release schedule, and continuous integration.
  • Guide and mentor junior team members to maintain SDLC, agile methodologies, designs that scale and codebases that make you proud.
  • Participate in daily stand-ups, story planning, reviews, retrospectives, and the occasional outings to nearby local cuisine and / or culture.
You have.
  • Education: B.S. / M.S. in data science, computer science, physics, electrical engineering, applied mathematics, or a related degree
  • Probability + Statistics: solid fundamentals in the areas of mathematics that allow us to interpret the world empirically. An empirical approach should inform everything you do.
  • ML: experience (>3 years) in developing machine learning applications
  • Fluency: In modern data languages: Python, Matlab, Scala or a few others (we like R and Julia).
  • Agile-minded: fan of TDD and agile methodologies
  • Data wrangler: Passionate about data and the ability to use data to understand systems
  • Algorithms / Data Structures: Design patterns, efficiency, using the right abstraction for the task
  • Functional Programming: filters and maps, currying and partial evaluation, group-by and reduce-by, oh my!
Bonus points for:
  • Data visualization: matplotlib / seaborn, D3js, ggplot, plotly
  • Google Cloud Platform: use of GCP to support ML systems
  • SQL: be well skilled in SQL, and knowledge of partitioning
  • Talking shop: around games of pool, and potentially other games that spontaneously erupt in the office
Perks and Benefits
  • Competitive Salary
  • Health / Dental / Vision
  • Flexible Spending Account
  • Commuter Benefits
  • Unlimited Vacation / Paid Holidays
  • Education / Tuition Assistance
  • 401K / Match
  • Generous Parental Leave
  • On Demand Learning (Udemy)
  • Team Lunches / Outings /Events (Yes! We found a way to do virtually!)
  • Offices (for when you want one)

At Bombora, we embrace diversity because it breeds innovation. Bombora is an equal opportunity employer and participates in E-Verify. Employment offers are contingent upon completion of successful background checks.

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