Constructor.io

Machine Learning Engineer (Recommendations)

в Constructor.io

7 500 —‍ 9 100 $/мес на руки

Полная удалёнка
Специализация
Data Science / Machine Learning
Уровень
Senior
Английский
B2 — Upper-IntermediateB2 — Upper-Intermediate

Constructor.io powers product search and discovery for the largest retailers in the world, serving billions of requests every year: you have most likely used our product without knowing it. Each year, we are growing in revenue and scale by several multiples, helping customers in every eCommerce vertical around the world.

We love working together to help each other succeed and are committed to maintaining an open, cooperative culture as we grow. We get the right answer with empathy, ownership, and passion for making an impact.

The Recommendations team, within the Engineering Department, plays an important role in implementing algorithms that optimize for business KPIs like revenue & conversions for our Recommendations product. We focus on metrics over features, arming our recommendation algorithms with powerful capabilities that bring value to customers in the way they care the most about it.

The team consists of a mix of designers, full-stack, and machine learning engineers who own and collaborate on multiple projects. As a member of the Recommendations team, you will participate in defining our product strategy & prioritization, as well as use world-class analytical, engineering & machine learning techniques to evolve and scale our recommendation algorithms.

Stack

PythonSQLSparkPresto/AthenaHive

Challenges you will tackle

  • Create a cutting-edge personalized recommendation system using ML, engineered to handle over 100 million requests per day seamlessly.
  • Design & deliver new recommendation features & products to satisfy customer needs & drive revenue growth efficiently.
  • Improve business KPIs by validating hypotheses with new recommendation features & techniques.
  • Participate in strategic planning, brainstorming & prioritization sessions to improve the recommendations' product.
  • Collaborate with technical and non-technical business partners to develop analytical dashboards that describe the impact of recommendations to stakeholders.

Requirements

  • You have a strong knowledge of machine learning fundamentals.
  • You excel at Python, have proficiency with any variant of SQL, and feel comfortable with the big data stacks like Spark, Presto/Athena & Hive.
  • You have delivered production ML systems and conducted A/B tests to validate their value.
  • Excellent English communication skills.
  • Passion for helping others grow and succeed as developers.
  • Data-driven mindset, with a passion for experimenting and using customer feedback to drive decision-making.
  • Strong strategic planning and prioritization skills.
  • Continuous learning and tracking of recent advancements in the field of AI and ML.

Also, nice to have

  • Experience building recommendation or ranking systems.
  • Experience with building high-load real-time ML systems.
  • Proficient in server-side coding for web services and understanding API design principles.
  • Experience with NoSQL, distributed systems, and caching solutions.

Benefits

  • Unlimited vacation time — we strongly encourage all of our employees to take at least 3 weeks per year.
  • A competitive compensation package, including stock options.
  • Fully remote team — choose where you live.
  • Apple laptops are provided for new employees.
  • Training and development budget for every employee, refreshed each year.
  • Parental leave for qualified employees.
  • Work with smart people who will help you grow and make a meaningful impact.
  • Compensation: base range of 80-110K USD + stock options.
  • Work from home stipend! We want you to have the resources you need to set up your home office.
Emma Haskins Talent Acquisition Manager
Constructor.io

О компании Constructor.io

Сфера
Продуктовая компания
Размер
201 - 500

Constructor.io делает платформу product discovery (поиск, рекомендации и многое другое) as a service для e-commerce. Среди клиентов Sephora, Petco, home24, Birkenstock. Недавно подняли очередной раунд.

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