• Full Time
  • Anywhere

Wikimedia Foundation

Summary

The Wikimedia Foundation is looking for a Senior Machine Learning Engineer to join a small team spread across UTC -5 to UTC +3 (East Coast US, Europe, and Africa) and will report to the Director of Machine Learning.  As a Senior Machine Learning Engineer, you will be responsible for planning, developing, documenting, deploying, and managing production machine learning models. In this role, you will work with product teams, SREs, researchers, and the volunteer community on machine learning models making Wikipedia and similar projects better. One day you might work on taking a model in a Jupyter Notebook created by Wikimedia’s Research Team and re-implementing it as a scalable production machine learning model to predict whether an edit is vandalism, the next day you might help volunteers contribute to our machine learning models already in production.

You are responsible for:

Working with internal customers (e.g. Wikimedia researcher who have created a proof-of-concept of a model) and external customers (e.g. Wikipedia editors and other volunteers) to deploy and manage productionized, scaled machine learning models.
Skills and Experience:

5+ years of experience in an MLE/MLOps role as part of a team deploying production models.
Experience with end-to-end deployment of production machine learning models
Strong English language skills and ability to work independently, as an effective part of a globally distributed team
Qualities that are important to us:

Professionalism
Positivity and solution focused
Independently motivated
Commitment to the mission of the organization and our values
Commitment to our guiding principles
Ability to disagree in a respectful manner and yet work towards a solution even when you disagree
Good at async communication
Solutions-focused.
The Wikimedia ecosystem is complex, resources are limited, and our guiding principles are ambitious. We want you to work to find solutions embracing these factors.
Self motivated with an ability to navigate through ambiguity and bring a project to completion with limited directions
Curiosity and commitment to learn.
Additionally, we’d love it if you have:

Experience with Docker, Kubeflow, or other MLOps systems
Experience with volunteer communities and open source software development
Experience with global coworkers
Experience with remote work and/or async work
About the Wikimedia Foundation

The Wikimedia Foundation is the nonprofit organization that operates Wikipedia and the other Wikimedia free knowledge projects. Our vision is a world in which every single human can freely share in the sum of all knowledge. We believe that everyone has the potential to contribute something to our shared knowledge, and that everyone should be able to access that knowledge freely. We host Wikipedia and the Wikimedia projects, build software experiences for reading, contributing, and sharing Wikimedia content, support the volunteer communities and partners who make Wikimedia possible, and advocate for policies that enable Wikimedia and free knowledge to thrive. 

The Wikimedia Foundation is a charitable, not-for-profit organization that relies on donations. We receive donations from millions of individuals around the world, with an average donation of about $15. We also receive donations through institutional grants and gifts. The Wikimedia Foundation is a United States 501(c)(3) tax-exempt organization with offices in San Francisco, California, USA.

As an equal opportunity employer, the Wikimedia Foundation values having a diverse workforce and continuously strives to maintain an inclusive and equitable workplace. We encourage people with a diverse range of backgrounds to apply. We do not discriminate against any person based upon their race, traits historically associated with race, religion, color, national origin, sex, pregnancy or related medical conditions, parental status, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, or any other legally protected characteristics.

If you are a qualified applicant requiring assistance or an accommodation to complete any step of the application process due to a disability, you may contact us at recruiting@wikimedia.org or +1 (415) 839-6885.

U.S. Benefits & Perks*

Health Care Benefits Covered at 100%: We cover 100% of premiums for medical, dental and vision plans for all full time employees and eligible dependents
Wellness Reimbursement Program: Up to 1,800.00 USD per year for reimbursement for staff wellness expenses, such as gym fees, educational expenses, and more
Technology and Equipment Stipend: In addition to receiving a brand new laptop, monitor, & docking station, all new hires receive 600.00 USD stipend to set up their space for working virtually 
Professional Development Program: Up to 750.00 USD reimbursement per year to encourage continuous learning through attending conferences, courses, workshops and the purchase of educational materials 
401(k) Retirement Plan: Employer match of up to 4% of employee contributions dollar for dollar with no vesting period
Paid Time Off: Generous paid time off policy of over 45 days, which includes: vacation days, at least one observed holiday a month, sick leave, and volunteer days
Flexible Schedules: Options available to balance your personal and remote-work life
New Parent Leave: Fully paid new parent leave for seven weeks plus an additional five weeks for pregnancy, and flexible options as you embark on your return to work
Fertility and Adoption Reimbursement Plan: Reimburses staff up to 5,000.00 USD in expenses per year, with a lifetime maximum of 10,000.00 USD
Assistance for those unexpected life events: Long and short term disability, life insurance, and an employee assistance program
Pre-tax Savings Plans: Generously funded health savings accounts (HSAs), pre-tax contribution options for health care, child care & elder care, public transportation and parking expenses
*Please note that for remote roles located outside of the U.S., we defer to our PEO (Professional Employee Organization) to ensure alignment with local labor laws.

To apply for this job please visit grnh.se.