Upwork ($UPWK) is the world’s work marketplace. We serve everyone from one-person startups to large, Fortune 100 enterprises with a powerful, trust-driven platform that enables companies and talent to work together in new ways that unlock their potential.
Last year, more than $3.8 billion of work was done through Upwork by skilled professionals who are gaining more control by finding work they are passionate about and innovating their careers.
This is an engagement through Upwork’s Hybrid Workforce Solutions (HWS) Team. Our Hybrid Workforce Solutions Team is a global group of professionals that support Upwork’s business. Our HWS team members are located all over the world.
The ideal candidate for this role will have experience building solutions for machine learning solutions to tackle business challenges. You don’t have to have a degree from one of the world’s top schools, but you’ve already done a few big things in your career and can hang with some of the brightest machine learning engineers, managers and architects in the world. One of your hallmarks is your ability to reconcile business needs with what the data is suggesting to come up with new ideas and approaches for ML teams. In the process, you derive much of your joy at work knowing that your inventions and your job matters.
If you and the team you’re on are successful, you will change the company and the world.
As a Lead Machine Learning Ops Engineer, you’ll be responsible for creating and optimizing the overall solution for Machine Learning (ML) use cases and applications within the ML platform. Collaborating with Lead Engineers, Enterprise Architects and a wider range of colleagues within the community to coordinate strategies, and to develop new Analytics, Artificial Intelligence (AI), and ML solutions that are fit for purpose.
Must Haves (Required Skills):
Upwork is proudly committed to fostering a diverse and inclusive workforce. We never discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical condition), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.