{"id":2015065,"url":"https://alion.io/job/grindr-staff-machine-learning-engineer","title":"Staff Machine Learning Engineer","company":{"id":1763503,"name":"Grindr","domain":"grindr.com","url":"https://alion.io/company/grindr-com","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Welcome to the Jungle","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":208000,"max":244000,"currency":"USD","period":"year","gross":null,"usd_annual":244000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Helm","optional":false},{"name":"Keras","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2026-07-13T00:09:49Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-08T22:11:53Z","board_verified":true,"closed_at":null,"days_open":88,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":88},"description":"Join Grindr, the world's largest social networking app for the LGBTQ+ community, as a Staff Machine Learning Engineer. In this role, you will have a significant impact on the future of the platform by building scalable recommendation systems, leveraging the latest LLMs, and collaborating cross-functionally with engineering, data science, and product teams. You will also have access to a range of benefits, including 100% employer-paid medical, dental, and vision premiums, 401k matching, flexible PTO, and equity for all employees.\nMissions\nArchitect scalable recommendation systems to serve millions, balancing performance and innovation.\nPrototype, iterate, and ship production-ready ML solutions that solve real problems for our users.\nCollaborate cross-functionally with engineering, data science, and product teams to turn bold ideas into tangible results.\nProfil recherché\n - Experience with any public cloud environment - AWS, GCP or Databricks- Proven ability to deliver at scale, with fluency in Python and popular MLframeworks\n- A scrappy mindset-you tackle messy challenges head-on and get real results\n- Experience building machine/deep learning models with at least one common framework such as PyTorch, Tensorflow, or Keras\n- Experience using data and deployment technologies (Snowflake, Airflow, Kubernetes, Docker, Helm, Spark, PySpark)\n- Expertise in building and maintaining LLM workflows for nuanced, human-driven tasks\n- A track record of crafting recommendation systems that hit the mark for diverse user needs\n- Thrives in a fast-paced, outcome-driven environment with lots of cross-functional collaboration\n- 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\n- 7+ years of experience building ML systems with a focus on 0-to-1 system development and creating new capabilities from scratch. 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