Staff Machine Learning Engineer Dating Outcomes

• 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.

• 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.

What We Do

In today’s digital world singles are so focused on sending likes and looking through profiles that they’re not actually building meaningful connections and going on dates. Hinge is on a mission to change that by designing the most effective app experience. We want to create a less lonely world by inspiring intimate in-person connections. Relationships are at the core of everything we do. And not just the romantic kind. We can't accomplish really hard things alone - so we make great relationships the foundation of our teamwork. We believe these three core values are what it takes to build those great relationships: Authenticity we share - never hide - our words actions and intentions. Courage breakthroughs require a willingness to take risks and embrace lofty goals and tough challenges. Empathy we're all humans first. So we deeply consider the perspectives of others listen openly and speak with care.

Why Work With Us

We're mission-driven. While most apps think about boosting sessions and time on app we think strategically about meaningful end results (dates and relationships). We're culture-first. We believe in great people over process. Decisions are pushed to the front lines with feedback and coaching provided by our leaders.

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