Staff Machine Learning Engineer, Dating Outcomes
New York, New YorkFull-TimeStaffAI / Data Science
Responsibilities
- Design and own foundational research and models that power our recommendations ecosystem.
- Identify the next step change in our technical capabilities, conduct state-of-the-art applied research, and move them into production using best practices in machine learning engineering.
- Design and implement solutions that prioritize availability, scalability, operational excellence, and cost management, while delivering incremental impact to our daters.
- Collaborate closely with Directors and VP+ to understand and shape Hinge’s strategic direction, as well as work with other Machine Learning Engineers, Product Managers, Data Engineers, and Scientists to make that a reality.
- Coach, 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++ and a deep understanding of low-level deep learning computation fundamentals.
- System design & architecture: Proven track record of research, training, and deployment of DNNs at scale. Deep 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 various DNN architectures, track record of building, debugging, and fine-tuning models.
- DevOps skills: Track record of deploying, managing, and orchestrating offline and online deep learning models at scale.
- 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. Proven ability to influence company strategy and direction is a plus.
- 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.
- 8+ years of experience, depending on education, as an MLE.
- 4+ years of experience working in a cloud environment such as GCP, AWS, Azure, and with dev-ops tooling such as Kubernetes.
- 4+ years of experience in designing and developing online and production grade ML systems.
- 3+ years of experience leading projects with at least 2 other team members through completion.
- A degree in computer science, engineering, or a related field.
