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.
We encourage people from underrepresented groups to apply.
At Urbint, the machine learning team does not work on making consumers spend more or on maximizing clicks. That is all fine; we work on reducing carbon emissions, reducing infrastructure risk and avoiding fatalities. We find meaning and excitement solving these problems, and we hope you do, too.
We are looking for a Sr Machine Learning Engineer focused on MLOps to join our high visibility, high impact Machine Learning team to help with this mission. The ML team collaborates with a diverse, broader-mission team to deliver value for our customers. Members of the Machine Learning team have the option to major/minor in areas from a large data science specialization spectrum: Technical Product Management, People Management, Data Story-Telling, Applied ML, ML Research, AutoML (Algo/Performance) and MLOps (DE, SRE). This is a great role for someone who enjoys variety and is also looking to expand their skill set in a structured fashion.
What You’ll Do
- You will own the production Feature Store and Model Serving infrastructure.
- Develop self-service tools for data scientists that support feature engineering pipeline, model testing and deployment.
- Develop distributed training infrastructure (autoML) for faster training of models.
- Develop tools to monitor ML models in production, monitoring drift and performance.
- You may lead a team and will own key portions of department OKRs that help maximize team productivity.
- Overall, you will be responsible for delivering business value at scale via Machine Learning.
Who You Are
- 2+ years experience working in a DevOps or data engineer role using cloud-based infrastructure such as GCP (preferred), AWS or Microsoft Azure.
- 4+ Software development experience and strong design skills.
- Expert in Python, comfortable with Flask/Django and one high performing language.
- Exposure to machine learning concepts and interest in learning more.
- Familiarity with Kubernetes or other container orchestration tools in a production setting.
- Familiarity with workflow orchestration tools such as Airflow.
- Experience automating deployments in GCP (preferred), AWS or Azure.
- Up to date with what’s under the hood of some of the advanced ML infra tools available.
Nice to Have
- Experience building AutoML.
- Experience implementing algorithms from research papers and building models.
- Track record of creating excellent slack emojis and memes.
- 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
- We are 100% Distributed – work from almost anywhere
- Distributed work monthly stipend
- Office Space Stipend for co-working space expenses
- Wellness reimbursement
- Educational Allowance
- Weekly lunch stipend
Urbint’s Core Values
- Passionate about customers: We strive to deliver sustainable value and exceed expectations, and we’re not satisfied until our customers are raving fans.
- Be decisive: We make timely, informed, and pragmatic decisions to keep the organization moving forward.
- Build trust: Our values are the building blocks to trust. As we live them, we grow and build lasting relationships.
- Focus on impact: We measure and strive to continuously improve our real-world impact.
- Be tenacious: We are agile in our approach to addressing challenges but firm in our beliefs.
- Win together: We efficiently leverage our diverse skills and perspectives for one another, united by our shared vision.
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.