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Senior Machine Learning Engineer - Algs

Keebo

United States
  • Remote job

Keebo is a venture-backed startup that offers a turnkey cloud-based Data Learning platform for automating and accelerating enterprise analytics. With the data warehousing market expected to grow to $51B annually by 2028, Keebo is an industry innovator,  as the only fully-automated Snowflake optimizer, adjusting dynamically to save many customers 25% and more.

Built on state-of-the-art in machine learning and artificial intelligence, and over 15 years of cutting-edge research at top universities, Keebo reduces tedious and months-long manual operations to a matter of minutes, freeing up data teams to work on improving their core business. Our team is spread across the globe, supporting customers worldwide.

About the Opportunity

As a Senior Machine Learning Engineer on our Algorithms team, you will bring your expertise in machine learning and data science to help the team move faster and achieve critical revenue goals for Keebo. You will work closely with ML engineers and data engineers to evaluate algorithmic and business problems and apply your machine learning and software engineering skills to build reliable, repeatable models that run in production with high quality.

You Will

  • Research, implement, and tune cutting-edge RL/ML models to achieve critical business outcomes
  • Design and implement AI/ML models that balance quality, speed, and cost
  • Collaborate with the rest of the Algorithms team to achieve goals that drastically impact the revenue of the business
  • Build repeatable, reliable pathways for promoting ML models from development to production

You Have

  • Experience as a machine learning engineer, working on real-world problems impacting live customers
  • Experience developing ML models end to end and deploying into production environments
  • Experience building and maintaining scalable, reliable, and safe ML models that directly impact customers’ experience
  • Experience implementing AI/ML models that balance quality, speed, and cost
  • Experience automatically monitoring the quality and effectiveness of ML/AI models from local dev through to production
  • Experience with SQL, data analysis, and databases
  • Experience with Python, and strong track record of writing readable, maintainable production code
  • Experience with GCP or AWS
  • Skilled in being self-directed and moving quickly to build and improve systems and architectures
  • Ability to work in a fast-paced early stage startup
  • Skilled at communicating effectively in a distributed environment with people across multiple time zones
  • Strong self-motivation, initiative, and adaptability

Nice to Have

  • Experience with Java and Golang
  • Experience with Reinforcement Learning
  • Experience with Google Cloud and BigQuery

Our Environment

Keebo is a fully remote, global team with team members currently in the US, EU, and Canada.

What we Offer

Working with a world-class team of researchers and engineers in machine learning to turn Al algorithms into scalable and automated cloud products

For full-time positions:

  • Competitive salary packages
  • Equity
  • Home office stipend
  • Comprehensive medical, dental, and vision benefits
  • 401k retirement program
  • Annual company offsite (this year the team met up in Cancún, Mexico!)
  • Paid time off
  • Paid parental leave

Keebo is proud to be an equal opportunity employer and prohibits discrimination and harassment of any kind. We are committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, gender, national origin, age, disability, genetic information, or any other protected characteristic. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. We strive to create a diverse and inclusive workplace where everyone feels valued and respected. We encourage individuals from all backgrounds to apply.

Vacancy posted more than 2 months ago
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