Staff Machine Learning Engineer at Urbint
Staff Machine Learning Engineer
At Urbint, our mission is to make communities more resilient. We do this by pairing external data with artificial intelligence to identify areas of high risk and prevent catastrophic loss for utilities and infrastructure operators across the country. We are a team of close-knit engineers, entrepreneurs, and data geeks who obsess over problem-solving, new technologies, and making a positive impact in our communities.
Urbint is looking for a staff-level machine learning engineer to help guide our team’s effort on its next-generation machine learning platform. Urbint is a product with machine learning at its very heart; as a senior member of the ML team, job is to help refine this vision, continually making machine learning as impactful for our clients as it can be. Your will design and build machine learning tools to build models efficiently, effortlessly and predictably, models with a high degree of predictive accuracy. You will contribute to a strategy for collecting and fusing diverse sources of data to power our predictive systems, as well as building the tools needed for understanding the performance of models deployed in production settings. Finally, you will be a mentor, improving an already high-performing machine learning team through the breadth of your experience.
We encourage people from underrepresented groups to apply.
What You’ll Do
- Be a Technical Leader – Provide technical guidance to the team to build an infrastructure that helps scientists to build models, test hypotheses, run experiments, and deploy at scale in production environments.
- Explore Data – Understand and identify preliminary signals in the data prior to deep processing. Quickly analyze the dataset to assess its usefulness for machine learning.
- Prototype Models – Develop features, uncover patterns, and build models.
- Explore Techniques – From simple regressions to neural networks, we use a variety of techniques. You’ll have the freedom to explore multiple methods to squeeze insights out of data.
- Productize Models – A pattern is good, but a prescriptive solution is better. Build products that help our customers get the most out of their data and workflows.
Who You Are
- Masters in a quantitative discipline (e.g. Stats, Math, Physics, Engineering, CS, etc.)
- 8+ years of experience in data science/machine learning roles
- Experience solving concrete machine learning problems in diverse settings
- Advanced knowledge of machine learning methods and statistical principles, including experience in Bayesian statistics, anomaly detection, and/or time series forecasting
- Well versed in Python or R (and willingness to continue to learn the Python ecosystem)
- Proven experience designing and delivering solutions using large, diverse, real-world datasets to support business decisions
- Up to date with the current best tools and practices in the ML and data science ecosystems
Nice to Have
- Ph.D in a quantitative discipline
- Familiarity modeling with spatial data
- Experience doing machine learning on networks or in connected environments
- Mission Driven – Some companies use AI to serve better digital ads and trade stocks, we seek to make our communities safer and more resilient
- Top Compensation – Competitive compensation package
- Best in Class Medical Coverage – 100% benefits and premiums paid
- Health Perks – Wellness reimbursement and citibike membership
- Weekly lunch stipend
- Remote work monthly stipend
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