Industry leader in the Automotive ECommerce space, Publicly Traded, with 350M in the bank and growing rapidly undertaking a...
Industry leader in the Automotive ECommerce space, Publicly Traded, with 350M in the bank and growing rapidly undertaking a huge new platform build.
Our shopping experience helps buyers consider choices from every angle, builds confidence in their decisions, and enables every step of the process with tools and information that make car buying easy. Ultimately, we are helping people in the second largest purchase they will make in their lives. We're removing the complexity out of buying a car, using technology and personalization, to create a one-of-a-kind experience that transforms car buying and ultimately people's lives. Come join the team and help us accomplish our mission. We maintain a Dynamic Workplace, allowing employees to have their primary workstations at home, with office space in Santa Monica, CA and Austin, TX to be made available to individuals and teams to use as needed. Employees enjoy excellent benefits (health/vision/dental coverage, 401k with contribution matching, equity, etc.) as well as perks like monthly credits for at-home food delivery, internet/mobile phone service coverage, fitness expenses, and Caregiver support.
We are seeking to add Machine Learning Engineers to our Data team. This position requires a Machine Learning Engineer who can bring bleeding edge machine learning models into production together with a team of product analysts, data engineers, product managers and business domain experts.
What you'll do:
Partner with Data Engineering, Product and Design in a cross-functional agile team to deliver products that solve consumer problems in the automotive marketplace.
Write production ready high quality, maintainable and scalable code. Provide support on production issues as they arise.
Work on prediction algorithms, sorting algorithms, large-scale machine learning and recommendations and personalization.
Build simple yet functional models, deploy them early, and learn/iterate in order to continuously improve our products
Design and analyze metrics to verify model and algorithm effectiveness.
Keep up with the latest ML developments and evaluate how they can be applied to our products and business needs.
What you'll need:
5+ years experience in Machine Learning and AI at Big Data scale
Proficiency in Machine learning techniques like classification, regression, anomaly detection and clustering.
Strong programming skills with data analysis languages such as Python (PySpark) or Scala.
Hadoop/Spark and AWS experience.
Strong analytical and problem-solving skills.
Adapt messaging for varying audiences in the team, choose appropriate media and provide context
Ability to successfully collaborate with engineers within the team and help them learn and grow.
BA/BS in related field
Nice to have:
Strong background in algorithms, data structures, and object-oriented programming.
Experience in A/B testing of models and continuous deployment to production.
- provided by Dice