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.
As a Senior Data Engineer, you will bring your expertise in data engineering and ML Ops to help the team move faster and achieve critical revenue goals for Keebo. You will work closely with the AI engineers to understand their data and training needs, design and implement an improved ML platform that balances cost and speed of development, and have an opportunity to do AI/ML engineering yourself.
You Will
- Design and implement an AI/ML platform that balances speed of development with cloud costs
- Collaborate with the rest of the AI team achieve goals that drastically impact the revenue of the business
- Mentor AI engineers in data engineering and MLOps best practices
- Mentor engineers across Keebo in data engineering and architecture best practices
You Have
- Experience as a data engineer, building data pipelines, ensuring data quality, and implementing data modeling for use by ML/analytical models
- Experience with MLOps, including using automated testing and CI/CD to speed up model development
- Experience automatically monitoring the quality and effectiveness of ML/AI models from local dev through to production
- Experience with GCP or AWS
- Experience with Python and Golang, or similar
- Skilled in designing and implementing scalable, resilient data engineering and MLOps architectures that balance cost and speed of development
- Skilled in being self-directed and moving quickly to build and improve systems and architectures
- Strong communication skills and ability to advocate for data engineering best practices across the entire engineering organization
- Skilled in mentoring engineers in data engineering best practices
- 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
- Experience with Google Cloud
- Experience working as an ML/AI engineer in the past
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.
