Sr. Staff Machine Learning Engineer

Hiring Ranges:

Remote Germany: 130,000 EUR - 189,000 EUR

 

Why Mozilla?

Mozilla Corporation is the non-profit-backed technology company behind pioneering brands like Firefox, the privacy-minded web browser, and Pocket, a service for keeping up with the best articles online. More than 225 million people around the world use its products each month.

Along with 60,000+ volunteer contributors and collaborators all over the world, Mozilla Corporation’s staff are driven by our mission to ensure the internet is a global public resource, open and accessible to all. We design, build and distribute open-source software that enables people to enjoy the internet on their terms. 

About this team and role:

Fakespot is now part of Mozilla, where our mission to bring trust and transparency back to the eCommerce space is now aligned with ensuring the Internet is a global resource, open and accessible to all. Fakespot leverages machine learning, and other state-of-the-art technologies to detect spurious product reviews and vendors so consumers can make informed purchasing decisions based on real feedback by real people. Fakespot also facilitates the shoppers’ decision making process by utilizing language models to interactively summarize and highlight product features.  

At the Fakespot team, you will have the opportunity to play a crucial role in bringing trustworthy tools to millions of Firefox and Fakespot users.  By joining our team, you will be at the forefront of ethical and responsible AI, and contribute to a trustworthy Internet. 

What you’ll do: 

• Lead analytics projects, designing, developing, and deploying state-of-the-art machine learning models in line with business interests, particularly those related to enhancing the online shopping experience of our users 

• Harness your expertise in acquiring and processing large-scale and complex datasets from diverse sources, utilizing it for analysis and modeling by the team 

• Implement robust validation and testing procedures to ensure the developed models' generalizability and reliability

• Continuously monitor and optimize deployed models for performance and efficiency, and conduct troubleshooting when necessary

• Collaborate with other members in the data science team to brainstorm ideas, and search for optimal solutions  

• Work closely with the engineering, product management, and product design teams to deliver high-quality features and solutions

• Be involved in the full lifecycle of machine learning models, from development to deployment and monitoring, to ensure the models are effectively integrated into the production environment and continually optimized for performance

• Proactively stay abreast of the latest advancements in machine learning, natural language processing, and related fields to ensure our methodologies remain innovative and relevant

• Lead and mentor junior machine learning engineers, providing hands-on guidance where needed

What you’ll bring: 

• A bachelor’s degree in Statistics, Computer Science, related technical field, or equivalent practical experience

• A minimum of 5 years of experience in a quantitative role, ideally as a machine learning engineer or a data scientist

• Extensive knowledge of and experience with analyzing large-scale dataset utilizing statistical and machine learning tools

• Proficiency in a data query language (e.g. SQL), and a programming language (e.g. Python)    

• Extensive experience with deep learning frameworks (e.g. Pytorch, Tensorflow, Jax), and deep learning architectures (e.g. Transformer, RNN)

• Demonstrable experience with the full lifecycle of machine learning models - from development to deployment and monitoring

• Being goal-oriented with an independent problem solver with minimal supervision

• Enjoyment for taking ownership while engaging in collaborative efforts to fully comprehend the needs of other teammates

• Being an excellent team player with a proven ability to work effectively in cross-functional teams, showing a high degree of collaboration, flexibility, and respect for diverse perspectives

• Commit to our values:

• Welcoming differences

• Being relationship-minded

• Practicing responsible participation

• Having grit

Bonus Points For…

• An advanced degree (master or PhD) in a quantitative field

• Over 7 years of experience as a machine learning engineer or in a similar role

• A deep understanding of de