Senior ML & Data Engineer

Smarking is a leading provider of enterprise software and data technology solutions for the massively overlooked $655B global parking industry. With the post pandemic recovery across the industry, Smarking's Automated Yield Management (AYM) - the first Machine Learning (ML) based dynamic pricing engine in the parking industry - is gaining rapidly growing traction and requires systematic scaling to meet the market needs.

This is an excellent position for a highly capable software engineer who's passionate about scaling backend infrastructure, building and improving data and ML pipelines, refining machine learning algorithms, expanding integrations with our partners, and taking the Smarking AYM to the next level.

Reporting directly to the CTO, the Sr. ML & Data Engineer will work with  state-of-the-industry technologies including Python, Postgres, Flask, Docker, Redis, ElasticSearch, Airflow, Terraform, and AWS services such as EC2, S3, RDS, and ECS, and lead major engineering efforts that immediately impact our business and operations. Our infrastructure is cloud native, and we are moving towards a server less architecture.

KEY RESPONSIBILITIES

• Lead and execute mission critical software projects
• Scale Smarking AYM, an ML powered dynamic pricing engine on AWS
• Develop new integrations for AYM
• Refine ML algorithms for different industry cases
• Develop API and UI for end user facing manipulation of the pricing platform
• Other project opportunities may include: building distributed systems for real-time data streaming, anomaly detection, predictive analytics; scaling databases and backend services to handle rapidly growing data volume and API requests; expanding data integrations; and building internal tooling for data warehouses.

QUALIFICATIONS (EXPERIENCE)

• 5+ years professional software engineering experience
• 2+ years working on a SAAS product
• Desire to learn new technologies
• Strong experience with backend technologies including Python, Flask, Postgres, SqlAlchemy, Celery, Airflow
• Experience with data transformation, cleansing, and manipulation.
• Production-level experience with machine learning is a big plus.
• Strong communication skills with both technical and non-technical audiences.
• Knowledge about front-end stack (Javascript/CSS/React/Typescript) is a plus.

QUALIFICATIONS (CHARACTER)

• Hungry for responsibility, impact, and growth
• Humble, open-minded, and curious to learn
• Team first
• Strong sense of ownership
• Treat others with respect, empathy, and constructive candor

COMPENSATION

• Competitive salary and equity.
• 100% coverage of medical, dental, and vision insurances.
• 401K plan with 3% company hard match.
• $100 monthly data plan.
• $60 per month gym membership (or other physical activity)
• Unlimited paid time off.
• Expenses for setting up home-office.

About Smarking

Smarking is a group of passionate MIT PhDs, data scientists, Silicon Valley engineers, and battle-tested business professionals, committed to enable highly efficient urban mobility by building the digital infrastructure for the massively overlooked $655B global parking industry ($131B in the US).

Smarking is hired by organizations like Brookfield Properties, City of Miami, ABM Industry Groups, and many other enterprise industry leaders to turn their parking data into business results.  Smarking's dynamic pricing engine has been creating 40%-400% revenue uplift for online parking sales at parking facilities in Chicago, NYC, Boston, and many other cities, without any manual involvement required from property managers, leveraging fully automatic algorithm-driven yield management technologies similar to the airline and hotel industries. 

By providing the very first business intelligence and yield management enterprise SaaS to the parking industry, Smarking is establishing itself as an emerging leader in the US parking market. Smarking currently works with 2,500+ parking locations cross North America, based in San Francisco, and backed by top investors like Khosla Ventures and Y Combinator.