About The Role

Join Grindr, a unique platform at a global scale, as a Staff Machine Learning Engineer. In this early-stage role, you will have a significant impact on the company's long-term ML strategy. Your work will involve building scalable recommendation systems, leveraging the latest LLMs, and collaborating cross-functionally with engineering, data science, and product teams. You will also drive the exploration of emerging AI tools and techniques. Enjoy a range of benefits, including 100% employer-paid medical, dental, and vision premiums, 401k matching, flexible PTO, equity for all employees, and more.

Architect scalable recommendation systems to serve millions, balancing performance and innovation.
Prototype, iterate, and ship production-ready ML solutions that solve real problems for our users.
Collaborate cross-functionally with engineering, data science, and product teams to turn bold ideas into tangible results.
Experience with any public cloud environment - AWS, GCP or Databricks
Experience building machine/deep learning models with at least one common framework such as PyTorch, Tensorflow, or Keras
Proven ability to deliver at scale, with fluency in Python and popular MLframeworks
A scrappy mindset—you tackle messy challenges head-on and get real results
Experience using data and deployment technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, PySpark)
Expertise in building and maintaining LLM workflows for nuanced, human-driven tasks
A track record of crafting recommendation systems that hit the mark for diverse user needs
Thrives in a fast-paced, outcome-driven environment with lots of cross-functional collaboration
A proven history of taking product ownership and thoughtfully addressing the unique needs of a specific user group, from early-stage concept to full-scale rollout
7+ years of experience building ML systems with a focus on 0-to-1 system development and creating new capabilities from scratch. Experience with recommendation systems or similar is a plus

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