Data & ML Platform Engineer (Hybrid) - job 2 of 2

About Us

Our mission is to make small business teams unstoppable.

Homebase is the everything app for hourly teams, with employee scheduling, time clocks, payroll, team communication, HR, and more. More than 100,000 small (but mighty) businesses rely on Homebase to make work radically easy and give their teams superpowers. As the leader in small business team management, Homebase tracked 1+ billion hours for 2.5+ million workers last year.

Homebase is based in San Francisco, Houston, Denver, and Toronto. We are backed by leading venture investors L Catterton Growth, Emerson Collective, Notable Capital, Bain Capital Ventures, Khosla Ventures, Baseline Ventures, Cowboy Ventures, Bedrock Capital, and PLUS Capital.

👋 Hi, Future Homie! As a Homie, you'll be part of an unstoppable team that puts customers first, embraces each day with excitement, and strives for excellence in everything you do. We’re revolutionizing the way small businesses manage their teams and grow their business. What this means for you is a shared passion for innovation and making a difference for the people we serve.

So what do you say, will you join us on our mission to empower small businesses?

This platform engineer will be part of the team responsible for designing and implementing data and ML platform components to enable data engineering, data science, and product teams to build data- and ML-driven features, ensuring scalability, reliability, and seamless integration across workflows.

You will make an impact by:

• Design, develop, and optimize the ingestion of large volumes of structured and unstructured data from diverse sources.

• Support data architecture transformation initiatives on Databricks, ensuring scalable and efficient systems.

• Guide the design and implementation of platform components for the training, deployment, and monitoring of ML models in production environments.

• Provide expertise on industry best practices, tools, and technologies in ML engineering.

• Drive the continuous improvement of data and ML workflows through automation and innovative solutions.

• Take full ownership of projects, ensuring successful delivery from planning to execution.

• Collaborate with cross-functional teams to gather business requirements and translate them into effective technical solutions.

You are a bar raiser, this means you come with:

• 4+ years of  software development experience, specializing in data and ML

• Expertise in SQL, Python, and Databricks

• Experience with Airflow, Kafka, Redshift

• Proficiency in data modeling and database design.

• Experience having done data architecture transformations in Databricks

• Proficient in building and deploying machine learning models  (including language models) 

• Proficient in building model-serving pipelines for batch, streaming, and real-time inference

• Driving the operationalization of ML models, ensuring seamless deployment, monitoring, and continuous integration/continuous delivery (CI/CD) pipelines for ML systems.

• Strong problem-solving skills with a strategic mindset and attention to detail

• Effective communicator and collaborator across technical and non-technical stakeholders

Diversity, Equity, and Inclusion at Homebase

At Homebase, we take pride in fostering a welcoming space where every Homie of every gender, age, orientation, culture, and walk of life can be their full selves. Diverse perspectives empower us to build the best-in-class platform for small businesses and hourly shift workers. We recognize that experience comes in many forms, so if you think you’re close to what we’re looking for (even if you don’t meet 100% of the qualifications), we encourage you to apply!

**Interview Recording Notice:

By participating in interviews with Homebase, you consent to the use of Metaview, a recording and transcription tool, during the interview process. Please be aware that all interviews may be recorded and transcribed for the purpose of evaluating candidates and ensuring the quality of our recruitment process. If you do not consent to being recorded, please inform the Talent Team at the beginning of the call, and appropriate arrangements will be made to accommodate your preference. Your privacy is important to us, and the recorded interviews will only be used for internal evaluation and assessment of candidates.