Who we are:

Archipelago Analytics is a fast growing start-up working to revolutionize the quality of commercial property risk data and how it can be leveraged. Archipelago was founded in 2018 by tech and finance entrepreneurial veterans with previous leadership at RMS and Apple. We are an internationally diverse and remote-first company headquartered in San Francisco with additional offices in London, New York, India, and the Netherlands.

Who you are:

Archipelago is seeking an Engineering Manager, Machine Learning to join our growing team. As an Engineering Manager you will help lead a distributed team of machine learning engineers. We’re a small team distributed around the US & Europe, with headquarters in San Francisco. We iterate quickly, build for the long term, and are looking for smart, independent folks who want to ply their trade with like-minded people.

The ideal candidate will be comfortable working collaboratively, across teams & timezones, and helping us define our platform culture. You’ll have a significant impact, since the product & team is in its early stages. You’ll have a full team to support you, from research and design, through planning, development, deployment, delivery, and iteration.

The current Machine Learning team is located in the San Francisco Bay Area and London so we are considering candidates in the US, Canada, or UK.

Responsibilities: list all responsibilities

  • Lead a team of machine learning engineers.
  • Ensure quality and timeliness of shipped software.
  • Recruit, build, coach and mentor team; reinforcing software and machine learning engineering best practices
  • Be hands on enough that you can define architecture, contribute to code reviews, and ensure the health and scalability of ML models and application code .
  • Develop effective partnerships and collaboration with other teams at Archipelago.

Qualifications: list all qualifications

  • 5+ years of machine learning experience
  • 4+ years of experience managing a team or technical leadership
  • Strong track record of leading and delivering ML projects
  • Experience working in Enterprise software & data-heavy applications
  • Proficient in Python and Postgres
  • Experience working on high-performance technical teams and software engineering projects
  • Experience designing, building and debugging distributed systems
  • Familiarity with software engineering standard methodologies (e.g., design patterns, peer code reviews, unit testing)
  • Experience writing technical specifications and design documents
  • Ability to be flexible and adaptable in a dynamic start-up environment
  • You know how to communicate clearly no matter the medium: on Slack, task trackers, video calls, emails, in person, etc.
  • Strong desire to learn about new technologies and systems
  • Excellent time management and organizational abilities

Bonus Points:

  • Experience building software in the insurance, real estate, or finance industry
  • Experience architecting and deploying serverless infrastructure on the Amazon AWS platform

Benefits:

We offer benefits regardless of where you are in your career. We believe that providing our employees with the means to lead healthy balanced lives results in the best possible work performance.

  • Remote First Strategy
  • Company Equity Program
  • Medical, dental, vision and life insurance
  • Education and Enrichment
  • Generous paid time off upon hire – including a paid time off program plus eight paid company holidays
  • Mental Health programs
  • Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
  • Off-Archipelago - ½ day off every second Friday of the month
  • Remote office reimbursement
  • Team Offsites

*All benefits are subject to change at management’s discretion.

We are an equal opportunity employer with a commitment to diversity. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to age (40 and over), race, color, national origin, ancestry, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, religion, physical or mental disability, military or veteran status, genetic information, or any other status protected by applicable state or local law.