Communications Consultant

Job Description As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing. We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more. The Team or Role The Tinder ML team drives impact across nearly every core domain of the product — Recommendations, Trust & Safety, Profile, Chat, Growth, and Revenue optimization. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder’s ecosystem. ML at Tinder is organized into three groups with distinct roles: Machine Learning Engineers who focus on modeling and algorithmic innovation Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training, serving, and feature management Machine Learning Software Engineers who bridge the gap between research and production by delivering machine learning models into real‑world product experiences at scale About the Role We are looking for a Machine Learning Engineer II to help build and ship machine learning systems that improve product experience and drive measurable business impact. This individual‑contributor role focuses on modeling and algorithmic innovation. You will work closely with product, engineering, data, and platform partners to translate product opportunities into machine learning solutions, run experiments, and help bring models from development into production. The team’s work directly translates into measurable business outcomes, and many of its models are embedded in core Tinder user flows at scale. Where You'll Work This is a hybrid role and requires in‑office collaboration three times per week in Palo Alto, California. In this role, you will: Translate product and business problems into clear machine learning problems with measurable success criteria Build, train, evaluate, and improve production machine learning models Partner with software engineers and ML infrastructure engineers to deploy models and improve reliability, scalability, and performance in production Design and analyze offline evaluations and online experiments to understand model impact Contribute to feature engineering, data preparation, training pipelines, and model monitoring Write clean, maintainable, production‑quality code and participate in design and code reviews Communicate technical findings, trade‑offs, and recommendations clearly to both technical and non‑technical partners You’ll need: BS or MS in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field 1+ year of industry experience in machine learning, software engineering, data science, or a related field Strong foundation in computer science fundamentals, including data structures, algorithms, and software design Experience building ML or AI‑related systems, or strong understanding of how modern machine learning systems are developed and operated Proficiency in Python and at least one additional programming language such as Java, Kotlin, Go, Scala, or a similar language Strong understanding of machine learning fundamentals, including model training, evaluation, and experimentation Strong communication skills and the ability to collaborate effectively across functions Self‑motivated, proactive, and comfortable taking ownership of well‑scoped problems Salary The salary range for this position is $145,000 – $165,000 per year. This range reflects a role based in Palo Alto, California and is subject to geographic adjustment if the role is performed outside the listed location. As a full‑time employee, you’ll enjoy: Flexible vacation, 10 sick days Time off to volunteer and charitable donations matched up to $15,000 annually Comprehensive health, vision, and dental coverage 100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP) 100% paid parental leave (including for non‑birthing parents) and family forming benefits Investment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual $3,000 stipend for your professional development Investment in your wellness: access to mental health support via Modern Health, paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy Free subscription to Tinder Gold Commitment to Inclusion At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal‑opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Job Insights Learn more about the role and work environment by visiting our career page. #J-18808-Ljbffr Tinder