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 specially 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 Kubenetes 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.
Top Skills
What We Do
Match Group is home to some of the world’s most popular dating and social discovery apps, including Tinder, Hinge, Match, and more. Match Group’s mission is to spark meaningful connections for every single person worldwide. Our diverse portfolio of apps enables connections across a diverse range of ages, genders, backgrounds, and dating goals. Our services are available in over 40 languages to users all over the world.
Why Work With Us
Match Group is united by a mission to help people find meaningful connections and fight loneliness. We’re not just building products. We’re creating friendships, marriages, and families around the world. Our culture is fueled by purpose, creativity, and a passion for what we can build together.
Gallery

.png)





