Senior Machine Learning Engineer, Mozilla.ai
Performance-based bonus plans available
Democratizing open-source AI to solve real user problems
Open for applications
Democratizing open-source AI to solve real user problems
1-20 employees
Open for applications
Performance-based bonus plans available
1-20 employees
Company mission
To build, commercialize, and open source components and tools that make it easy for developers and users to develop AI agents to solve real-world use cases.
Role
Who you are
- +5 years of professional experience in machine learning and strong background software engineering
- Comfortable with open source development work
- Experience with deep learning frameworks, (e.g., PyTorch) is a plus
- Experience with large-scale dataset processing and data augmentation techniques
- Experience with managing experiments and models (e.g., platforms like Weights and Biases, MLFlow, KubeFlow)
- Strong proficiency in Python and familiarity with relevant libraries and tools
- Comfortable working in the cloud - containerization, cloud resource management, etc
- Excellent problem-solving skills and the ability to work both independently and as part of a team
- Effective communication skills, including the ability to translate technical concepts to non-technical stakeholders
- A demonstrated track record of delivering high-quality, scalable solutions in a fast-paced environment
What the job involves
- We are seeking a Machine Learning Engineer with a strong background in developing products with ML models at their core - areas like recommendation systems, scaled detection, feature extraction, content modeling, agents, natural language interfaces, search, etc., to join our dynamic team. The ideal candidate will be working on a product engineering team and contribute to our open-source LLM evaluation platform, focusing on model validation, selection, and deployment. The main responsibilities of this position are:
- Develop tools to streamline development, management, and/or evaluation of models
- Collaborate on the design and build end-to-end machine learning pipelines on cloud infrastructure
- Prepare and preprocess datasets for model evaluation
- Run and manage experiments related to model evaluation and training
- Evaluate model performance using standard metrics and techniques
- Collaborate with other teams, including product management and platform engineering, to ship features
- Collaborate on the implementation of MLOps best practices to ensure smooth model deployment, monitoring, and maintenance
- Engage with internal and external stakeholders, translating complex technical details into clear insights
- Contribute to the product engineering lifecycle, from ideation to deployment and maintenance of new features
Our take
The fever pitch for AI has led to a number of exciting new products and innovations that can enrich people's lives. Mozilla, however, doesn’t believe that human agency and user interest have generally been at the core of products like Chat GPT and the latest LLM models. Mozilla believes that accountability and transparency should be at the heart of this new technology. That’s why the legacy software company has launched Mozilla AI, a company dedicated to building an independent open source - and above all - trustworthy AI ecosystem.
Founded in 2023 off a $30 million grant from its parent company, Mozilla AI is focused on developing and investing in tools that make generative AI safer and more transparent. A response to the status quo of other large tech companies' approach to AI, Mozilla might be a little late to the game compared to Google and Apple, but this has allowed it time to innovate beyond the initial surge of products. One of its first releases was Fakespot, which uses an AI chatbot to weed out fake or deceptive user reviews in the eCommerce space, exemplifying its user-first ethos.
With its refreshing take on the AI revolution, Mozilla does have a lot of catching up to do. The proof of its people-first philosophy will come from future investments and products, and it’ll be interesting to see if it can live up to its industry-disrupting manifesto.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
47% female employees
Glassdoor (3.6)
Company
Funding (1 round)
Mar 2023
$30m
GRANT
Total funding: $30m
Company benefits
- Premium package featuring core benefits tailored to your country of residence encompassing essential services such as health insurance and retirement plans
- 25 per year of Paid Time-off
- Generous performance-based bonus plans to all regular employees
- One-time home office stipend of 1,000 USD
- Annual professional development budget
- Annual well-being stipend of 3,500 USD
Company values
- Trust - We believe that the lasting success of artificial intelligence hinges on the trust users can place in it. We work to bolster this trust, ensuring that such technologies empower their users first and foremost
- Social Impact - Impact is at the heart of our approach to technology. We strive to ensure that developed tools and systems are more accessible and beneficial for social good
- Transparency - By prioritizing transparent methodologies and tooling, we strive to build clearer views into the mechanics of AI systems, and seek to empower communities to engage, critique, and improve upon them
- Innovation - With an experimental mindset and a dedication to design thinking, we seek to shape emerging forms of artificial intelligence to be more human-centric
Company HQ
Argüelles, Madrid, Spain
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