A BIT ABOUT US

At CAPE, we pioneered the creation of property intelligence analytics through computer vision, machine learning, and geospatial imagery.
Property intelligence from CAPE allows insurance carriers to elevate their underwriting workflows, which consider a multitude of risk factors that determine each policy’s eligibility and price. CAPE’s low-latency APIs feed risk-relevant data into consumer shopping interfaces, programmatic underwriting workflows, and insurance pricing models. Our risk intelligence web portal provides a deep view into property-level risk for underwriters. CAPE’s products improve our clients’ underwriting efficiency and effectiveness and enable them to deliver superior experiences to their policyholders.
CAPE’s solutions have been adopted by leading insurance carriers across the U.S., Canada, and Australia…but we are just getting started. Over the past 10 years, we have constructed a risk analytics platform purpose-built for deep learning. Going forward, we set out to solve an even larger share of the problem, leveraging a radically expanded array of input data sources and advanced machine learning technologies.

THE OPPORTUNITY:

We are looking for a Staff Machine Learning Engineer with a passion for building practical, robust, and scalable machine learning solutions, and interacting cross-functionally with a variety of teams. Specifically, you will be responsible for improving and extending our core product offering. You will gain expertise in the full model development stack, from ground truth generation to in-depth model performance and proof-of-value analysis for our clients. You will also contribute to product research, ensuring that our machine learning solutions meet high standards while delivering maximum value to our clients.
At the staff level, you will also be responsible for assessing the feasibility of novel ML solutions (whether our engineers can build what is needed with the time, skills, and technology available), overseeing the work of others, and participating in product roadmap planning.

THE SKILL SET:

• PhD in a STEM field with 3 years of hands-on industry experience, or a Master’s degree in a STEM field with 7+ years of hands-on industry experience.
• Expert written and verbal communication skills, with the ability to understand and articulate business requirements and objectives to both technical and non-technical stakeholders.
• Advanced expertise of statistical techniques, including hypothesis testing, statistical sampling, significance testing, statistical inference, maximum likelihood estimation, and experimental design, among others.
• Advanced expertise of supervised and unsupervised algorithms and their implementations, machine learning concepts including regularization, learning curves, optimizing hyperparameters, cross-validation, among others.
• Advanced expertise with deep learning for computer vision.
• Advanced expertise in Python programming or other scripting languages including relevant libraries like numpy, pandas, SciPy, matplotlib.
• Advanced expertise of tools in the modern ML stack such as Spark, Jupyter, Docker, Git and cloud computing on AWS or GCP.
• Advanced expertise in building data tools for ETL, extracting data from SQL and NoSQL databases, and data analysis.
• Advanced expertise in building meaningful data visualizations.
• Experience with GIS systems is preferred.
• Experience in mentoring junior team members and leading projects.
• Ability to travel 1-2 times annually for company/team events.

Please refer the Job description for details