Senior Machine Learning Engineer, Dating Outcomes
New York, New YorkFull-TimeSeniorAI / Data Science
Responsibilities
- 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.
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, 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.
