Machine Learning Engineer
Montreal, Quebec, Canada - Remote
Founded in 2009, Dribbble is the top global community for designers and creative professionals and an inspiration destination for over a hundred million people every year. We're empowering creatives around the world to make a living doing what they love. Our mission is to provide support at every stage of a creative's journey; whether that's freelancing, selling their physical and digital goods on our marketplace, or being hired by some of the world's leading design-forward companies.
With many jobs, you have to pick between having a huge impact on the organization (small team) or having a huge impact on the world (big product), but at Dribbble - you get to do both, as part of a highly collaborative team, working on one of the world's top 1000 websites.
At Dribbble, we serve a global community and we need a diverse team to do that successfully. Women, people of colour, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. We provide an accessible candidate experience, and if you need any accommodations or adjustments throughout the interview process and beyond, please let us know. We're dedicated to fostering an inclusive and diverse environment for employees from all walks of life.
We’re building a fully remote team across North America (Canada & the US). We believe that creative collaboration can happen anywhere, and that working remotely shouldn’t have to mean sacrificing a sense of cohesion, community, and connection. We've seen that by combining thoughtful collaboration, frequent communication, and the freedom for people to be their authentic selves, you can do your best work and inspire others to do the same.
About the role:
At Dribbble, the Data team supports the entire organization along two core pillars.
1. Analytics: Enabling access to modelled, tested, and documented data, providing insightful reporting, supporting decision-making through research and analysis, and operationalizing analytics by deploying data to a collection of tools used by other functional teams internally.
2. Machine Learning: Developing production-facing solutions including search engines, ad serving, recommendation systems, content ranking systems, fraud detection, and more.
We are looking for a Machine Learning Engineer to expand our data product and bring new machine learning solutions to production. Dribbble has access to rich sources of user content and behaviour that we want to leverage to support our mission of empowering designers and creative professionals in their journey.
You will be reporting to the Director of Data Science, and collaborating closely with Product and Engineering to design, prototype, deploy, and maintain production-facing systems.
This is an exciting opportunity to further build the machine learning function at Dribbble!
As a Machine Learning Engineer, you'll be responsible for:
- Designing, developing, testing, and deploying new functionality in a Python RESTful service that drives Dribbble’s search engine, ad serving, and other solutions.
- Designing, training, and deploying machine learning models to production.
- Collecting and analyzing data to assess and improve the performance of our machine learning solutions.
- Collaborating with Engineering, Product, and other stakeholders to scope, explore, prototype, and implement solutions.
We're looking for:
- Software engineering experience. You have experience building large and scalable production-facing applications that are tested, documented, and version-controlled. Experience with RESTful web services, and technologies such as Elasticsearch, Redis, Kinesis, and Docker is a plus.
- Advanced knowledge in Python. You know the ins and outs of Python. Concepts such as list comprehensions, decorators, context managers, class inheritance and composition are no secrets to you. Experience with some of these frameworks and technologies is a plus: Flask, Celery, SQLAlchemy, Numpy, scikit-learn, TensorFlow.
- Machine Learning experience. You have experience designing, training, and deploying statistical and machine learning models using frameworks such as Scikit-learn, TensorFlow, Gensim, statsmodels.
- Stellar verbal and written communication skills. You can easily communicate complex and technical topics; you have excellent verbal and written communication skills.
- Excellent problem-solving skills. You come up with creative solutions to challenging problems.
Benefits
At Dribbble, you’ll join a diverse team dedicated to learning, teaching, and growing; as individuals, as a team, as a business, and as a community. As a workplace, we pride ourselves on doing right by our employees, and have a benefits package that makes being a part of the Dribbble team a dream job and something to be really proud of:
- 100% remote: so you can work where you feel most comfortable and inspired.
- Stay healthy: generous medical and dental for both you and your dependents.
- Relax and unwind: with plenty of paid vacation, and paid sick time for when you need it.
- Paid volunteer days: for you to spend giving back to non profits/organizations that are important to you.
- Celebrate: we observe both US and Canadian holidays - and a whole week of rest in December.
- Family leave: Paid time off for when your family grows.
- Save up: put pre-tax savings into a 401k/RRSP - we’ll match a portion of your contributions.
- Fitness fund: to help you feel your very best.
- Equipment fund: so you can deck out your home office.
- Monthly coffee budget: Grab that latte - it’s on us.
- Learning and development: Keep growing with paid courses, books, and conferences.
- Hang out: we get together at least once a year for some in-person face time.
- Pro tools: MacBook Pro (or Air) and all the tools you need to do a great job.
* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net
Tags: Docker Elasticsearch Engineering Flask Kinesis Machine Learning NumPy Python Research Scikit-Learn TensorFlow Testing
Perks/benefits: 401(k) matching Career development Conferences Flex vacation Gear Medical leave
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