Staff Data Engineer at Jobot
San Francisco, CA 94107
About the Job
This Jobot Job is hosted by: Christina Finster
Are you a fit? Easy Apply now by clicking the "Quick Apply" button
and sending us your resume.
Salary: $149,000 - $230,000 per year
A bit about us:
Our client is a top-rated AI-powered customer engagement platform that helps enterprise companies activate customers with jobful interactions at scale.
Why join us?
Perks & Benefits:
Paid parental leave
Competitive salaries, meaningful equity, & 401(k) plan
Medical, dental, vision, & life insurance
Balance Days (additional paid holidays)
Fertility & Adoption Assistance
Paid Sabbatical
Flexible PTO
Monthly Employee Wellness allowance
Monthly Professional Development allowance
Pre-tax commuter benefits
Complete laptop workstation
Job Details
How you will make a difference:
Own the Spark pipelines at the core of our ML platform in Databricks and optimize for scale, performance, and cost
Determine the best way to handle Iterable’s unique data model, including the intricacies of our customer’s unstructured data
Design end-to-end machine learning systems, including data acquisition, data cleaning, data models, model training, model serving, and evaluation
Build and own the batch and real-time feature stores that house our ML models
Work closely with the Iterable engineering team to improve our machine learning infrastructure and data quality
Build, evaluate, and integrate new models that add intelligence to our core product
Improve our model performance tracking system
Collaborate with leadership, senior teammates, and product managers to create product and technical roadmaps for features and products as part of Iterable AI
We are looking for people who have:
Data expertise: You have built and managed highly scalable data processing solutions (e.g. Spark, Flink), data lakes or warehouses (e.g. Databricks, Snowflake), authored queries (SQL), used workflow management (e.g. Airflow), and have experience maintaining the infra that supports these. You’ve tackled problems involving unstructured data in big data systems.
Experience building and scaling backend systems: You understand how different parts of the system work together, from data model to user interface, and have an understanding of distributed computing. You have a strong understanding of system design, data structures, and algorithms. Extensive experience with Scala or Python, with a preference for Scala competency.
Understanding of ML Platform Tech Stack: Demonstrated expertise in how data flows to and from a machine learning tech platform. Knowledge of statistics, and modern and classic machine learning techniques.
Empathetic Communication: You communicate nuanced ideas clearly, whether you're explaining technical decisions in writing or brainstorming in real-time. You assume the best intentions from your teammates and engage thoughtfully with other perspectives.
Bonus Points:
Experience building and supporting complex and modern end-to-end ML systems, like LLM pipelines
AWS experience
Experience in a SaaS environment
Experience with Akka libraries, especially Akka streams
Experience with IaC (Terraform preferred)
Exposure to marketing technology
Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.
Are you a fit? Easy Apply now by clicking the "Quick Apply" button
and sending us your resume.
Salary: $149,000 - $230,000 per year
A bit about us:
Our client is a top-rated AI-powered customer engagement platform that helps enterprise companies activate customers with jobful interactions at scale.
Why join us?
Perks & Benefits:
Paid parental leave
Competitive salaries, meaningful equity, & 401(k) plan
Medical, dental, vision, & life insurance
Balance Days (additional paid holidays)
Fertility & Adoption Assistance
Paid Sabbatical
Flexible PTO
Monthly Employee Wellness allowance
Monthly Professional Development allowance
Pre-tax commuter benefits
Complete laptop workstation
Job Details
How you will make a difference:
Own the Spark pipelines at the core of our ML platform in Databricks and optimize for scale, performance, and cost
Determine the best way to handle Iterable’s unique data model, including the intricacies of our customer’s unstructured data
Design end-to-end machine learning systems, including data acquisition, data cleaning, data models, model training, model serving, and evaluation
Build and own the batch and real-time feature stores that house our ML models
Work closely with the Iterable engineering team to improve our machine learning infrastructure and data quality
Build, evaluate, and integrate new models that add intelligence to our core product
Improve our model performance tracking system
Collaborate with leadership, senior teammates, and product managers to create product and technical roadmaps for features and products as part of Iterable AI
We are looking for people who have:
Data expertise: You have built and managed highly scalable data processing solutions (e.g. Spark, Flink), data lakes or warehouses (e.g. Databricks, Snowflake), authored queries (SQL), used workflow management (e.g. Airflow), and have experience maintaining the infra that supports these. You’ve tackled problems involving unstructured data in big data systems.
Experience building and scaling backend systems: You understand how different parts of the system work together, from data model to user interface, and have an understanding of distributed computing. You have a strong understanding of system design, data structures, and algorithms. Extensive experience with Scala or Python, with a preference for Scala competency.
Understanding of ML Platform Tech Stack: Demonstrated expertise in how data flows to and from a machine learning tech platform. Knowledge of statistics, and modern and classic machine learning techniques.
Empathetic Communication: You communicate nuanced ideas clearly, whether you're explaining technical decisions in writing or brainstorming in real-time. You assume the best intentions from your teammates and engage thoughtfully with other perspectives.
Bonus Points:
Experience building and supporting complex and modern end-to-end ML systems, like LLM pipelines
AWS experience
Experience in a SaaS environment
Experience with Akka libraries, especially Akka streams
Experience with IaC (Terraform preferred)
Exposure to marketing technology
Interested in hearing more? Easy Apply now by clicking the "Quick Apply" button.
Salary
149,000 - 230,000 /year