Machine Learning Engineer, Dating Outcomes - New York - Hinge

Description

Overview

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 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 work on modeling work end to end, including work on recommendation systems, multi-modal embedding, and generative models. You will be moving your research into production, both offline and real-time inference endpoints that directly impact the experience of millions of users. This is a fast-growing team, and you will have the opportunity to work with and learn from senior researchers and engineers.

Responsibilities

• 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.)
• Build systems with availability, scalability, operational excellence, and cost management in mind
• 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
• Work within our AI platform team to move models to production, monitor them, and make improvements to our serving infrastructure

What We\'re Looking For

• 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 and inference
• Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, 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, recommender systems are a plus
• Dev-ops 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
• 2+ years of experience, depending on education, as an MLE
• 1+ years of experience working on a cloud environment such as GCP, AWS, Azure, and with dev-ops tooling such as Kubernetes
• 1+ years of experience designing and developing online and production grade ML systems
• 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+, R aices , Women/Nonbinary, Parents —that hold regular meetings, host events, and provide dedicated support to the organization & its community.

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

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Factors such as scope and responsibilities of the position, candidate\'s work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment, if an authorization is granted to work outside of the location listed in this posting.