Senior Machine Learning Engineer, Dating Outcomes - job 1 of 2

Hinge is the dating app designed to be deleted

In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all.

About the Role:

The Dating Outcomes group is responsible for ensuring that people see their most compatible matches, helping them present themselves more effectively, and start meaningful conversations when they match. In short, we help people go on great dates!

We are hiring Staff Machine Learning Engineers to help us build the foundations of an AI first dating experience using the latest advancements in the field, leveraging Hinge’s years of preference data. You can expect to build recommendation systems end to end, experiment with using LLMs, photo and mixed input embedding models, as well as build and deploy real-time predictive models that directly impact the experience of millions of users. This is a fast-growing team, and you will have the opportunity to own and define the strategy, vision, and plan for accelerating machine learning at Hinge.

• Own and contribute to foundational models that power our recommendations ecosystem.
• Contribute to the research and development of models powering Hinge and experiment with the latest innovations in the field of Machine Learning (e.g., LLM agents, MMoE models, VAEs, etc.)
• Design, advocate for, and implement solutions that ensure availability, scalability, operational excellence, and cost management, while delivering incremental impact to our daters.
• Collaborate closely with other Machine Learning engineers, Product Managers, Data Engineers, and Scientists to understand our users' needs and identify opportunities to make their experience better through machine learning.
• Mentor and educate Machine Learning Engineers on current and SOA research, technologies, and best practices of practicing machine learning at scale.

• Strong programming skills: Proficiency in languages like Python, Java, or C++
• System design & architecture: Proven track record of training and deploying large scale ML models, especially DNNs. Good understanding of distributed computing for learning, data processing, and inference.
• Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, Databricks, KubeFlow, or W&B is a plus.
• ML knowledge: Deep understanding of DNN architectures, track record of building, debugging, and fine-tuning models. Familiarity with PyTorch, TF, knowledge distillation, and recommender systems is a plus.
• DevOps skills: The ability to establish, manage, and use data and compute infrastructure such as Kubernetes and Terraform.
• Data engineering knowledge: Skills in handling and managing large datasets, including data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow.
• Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.
• Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation
• Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes.
• 4+ years of experience, depending on education, as a Machine Learning Engineer.
• 2+ years of experience working in a cloud environment, such as GCP, AWS, or Azure, and with DevOps tooling, including Kubernetes.
• 2+ years of experience designing and developing online and production grade machine learning systems.
• 1+ year of experience leading projects with at least 1 other team member through completion.
• A degree in computer science, engineering, or a related field.

As a member of our team, you’ll enjoy:

401(k) Matching: We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year.

Professional Growth: Get an annual Learning & Development stipend once you’ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day.

Parental Leave & Planning: When you become a new parent, you’re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.)

Fertility Support: You’ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible.

Date Stipend: All Hinge employees receive a $100 monthly stipend for epic dates– Romantic or otherwise. Hinge Premium is also free for employees and their loved ones.

ERGs: We have eight Employee Resource Groups (ERGs)—Asian, Unapologetic, Disability, LGBTQIA+, Raices, Women/Nonbinary, Parents —that hold regular meetings, host events, and provide dedicated support to the organization & its community.

At Hinge, our core values are…

Authenticity: We share, never hide, our words, actions and intentions.

Courage: We embrace lofty goals and tough challenges.

Empathy: We deeply consider the perspective of others.

Diversity inspires innovation

Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.

If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know.

#Hinge