Research & Development

Machine Learning/Data Engineer (Remote)

Remote   |   Full Time

Company Profile

FindMine is the world's leading company helping iconic brands scale their editorial point of view. Our content engine uses machine learning to predict what a creative team member inside the brand would create, then amplifies, distributes, and measures all the existing and new content created. The result is maximized team productivity (90% time savings for merchants, marketers, personal shoppers, and store associates), higher Gross Margins and Customer Lifetime Value, and maximized sell-through. 


FindMine has won numerous awards and has been featured by Women's Wear Daily, CBInsights, Fox, VentureBeat, National Retail Federation, and is a Gartner “Cool Vendor.” FindMine is an equal opportunity employer and is the winner of Mogul’s Top Places to Work for Millennial Women. We value a diverse workforce. Women, people of color, members of the LGBTQ community, individuals with disabilities, and veterans are strongly encouraged to apply. 

Role Description

The company seeks a Machine Learning & Data Engineer who will own the machine learning initiatives, data pipeline, processing and storage required by the FindMine platform’s real-time recommendations engine.

The candidate should be a self-starter, with significant prior experience working in a start-up environment, ideally for a SaaS or API-focused company. The candidate will need to have hands-on experience building machine learning models to drive the core product forward, and will lead the charge in evaluating new technical ML/AI approaches from industry whitepapers or other research materials, create a plan to execute, develop the models, and perform a significant amount of development work to deliver these implementations.

The candidate should be able to quickly assess which approaches and models make the most sense and iterate and test on the hypotheses created.  A concrete example of this might be coming up with a hypothesis around what the right mix of NLP versus computer vision is optimal for driving the best results, evaluating the cost-benefit analysis of using/building/buying certain models, prioritizing which to work on first, building, testing and iterating the models, building the models themself, deploying the work into the production environment and evaluating performance of this mix.

Additionally, the engineer will be required to own the data pipeline infrastructure, which requires designing and maintaining the data flow of millions of operations in a scalable and asynchronous way. The candidate will also need to support the product and customer support teams to be able to generate scalable and efficient reporting of the data.

The ideal individual has served in a high-paced, complex, start-up environment long enough to have built something, seen it break, and fixed it.  The candidate is comfortable operating with a certain amount of ambiguity and is excited to jump into the company’s technology to make recommendations and optimize performance of their core offerings and efficiency of the team.

The candidate should also have a natural ability to coach and share their knowledge and communicate complex concepts in easily understandable terms for other technical and non-technical team members. Some customer facing meetings will required, so fluent spoken English is needed.

This position is fully remote for the foreseeable future.

Required Technical Skills

  • Python (3/5)

  • MySQL (2/5)

  • BigQuery/RedShift (2/5)

  • ELK Stack (2/5)

  • Scikit Image and Scikit Learn (4/5)

  • Airflow (3/5)

Nice to Have Skills

  • Datadog

  • Celery

  • Redis

Company Offerings

  • Competitive startup salary and equity

  • Medical/dental/vision benefits

  • An opportunity to work closely with our executive team and participate in many facets of the business

  • A chance to make a strong impact with your contributions as a key part of our company growth

  • A fun and flexible work environment with truly nice people where you can bring your whole self to work 

  • Monthly company fun events, including quarterly volunteering

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