Ping Data is a transformative 3-year-old startup in the property insurance sector. At Ping, we leverage advanced ML technologies and data extraction methods to extract and enrich property insurance data at scale. Our robust growth mirrors a startup that's aggressively investing in expansion, yet we maintain the stability of a self-funded, profitable enterprise.

Role Overview:

As a Senior Machine Learning Engineer, you will be pivotal in building and enhancing the core ML systems that extract data from a variety of noisy, semi-structured documents. You will have access to large datasets of raw documents and you have the autonomy to procure new data resources or annotations as needed. This role allows you to shape the direction of Ping's ML initiatives, enhancing tools and processes utilized across the ML team.

Responsibilities:

Design, build, and optimize ML systems for data extraction from multimodal documents.
Lead ML projects from conception to deployment, including opportunity identification, data collection, experimentation, production rollout, and post-launch monitoring.
Use the best tool for the job, whether it's an LLM, a classical tabular data method, or something else.
Evaluate existing production systems. Understand the characteristics and tradeoffs to achieve incremental gains.
Employ technologies like ONNX and Triton to enhance system throughput while minimizing resource usage.
Develop and refine Ping's model authoring and deployment tools.

Qualifications:

Master's or PhD degree in a related field such as computer science, machine learning, or data science is required.
Minimum 2 years of experience in machine learning, with a track record of deploying ML models to production.
Strong background in applying ML techniques to complex, real-world problems.
Preferable: proven track record of significant publications

Tech Stack:

Pytorch, 🤗 Transformers, Label Studio, Terraform/AWS, Python/Django/DRF, React/Redux/Typescript, Kubernetes/ECS, Redis, PostgreSQL.

Why Join Ping:

Be among the first to influence the ML team's direction and the broader engineering culture at Ping.

Work with a top-tier team of insurance and tech veterans in a market where Ping is poised for significant impact.

We are fully remote and we accommodate various time zones and working hours.