**Company: Mozilla.ai Job Description Summary: Qualifications: The ideal candidate for the Machine Learning Engineer position at Mozilla.ai should have a strong background in machine learning, NLP, and deep learning. Proven experience in developing and fine-tuning language models, particularly using PyTorch, is required. Experience with large-scale dataset processing and data augmentation techniques is also needed. Proficiency in Python and familiarity with relevant libraries and tools is a must. Knowledge of APIs and cloud computing platforms like AWS and GCP is important, with experience in containerization technologies like Docker being a plus. Effective problem-solving skills, the ability to work independently and as part of a team, and excellent communication skills are also necessary. A demonstrated track record of delivering high-quality, scalable solutions in a fast-paced environment is essential. Senior-level experience with 5+ years is preferred. Job Description: About Us: Mozilla.ai is at the forefront of the AI revolution, advocating for a decentralized and open-source approach. Our ambition is to empower developers to craft AI solutions that are both scalable and trustworthy. Through innovation, collaboration, and responsible AI practices, we’re shaping an AI future anchored in user agency, privacy, and transparency. • Position: Machine Learning Engineer • Location: Remote (EU, UK, Canada, USA) • Type: Full-Time Position Overview: We are seeking a skilled Machine Learning Engineer with a strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) to join our team. The ideal candidate will work with foundational OSS language models and specialize them. The candidate will prepare datasets for fine-tuning, evaluate results, and serve the models for production. The main responsibilities of this position are: • Develop and implement use cases involving language model fine-tuning and validation. • Prepare and… preprocess datasets for model fine-tuning and training. • Fine-tune OSS foundational models for domain specific tasks. • Evaluate model performance using standard metrics and techniques. • Design and deploy scalable and efficient NLP pipelines on our cloud infrastructure. • Develop APIs for dataset management and model serving. • Collaborate with cross-functional teams to integrate NLP functionalities into the main product. • 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. • Comfortable working on tooling to enable any of the above Qualifications: • Strong background in machine learning, NLP, and deep learning. • Proven experience developing and fine-tuning language models, particularly using PyTorch. • Experience with large-scale dataset processing and data augmentation techniques. • Experience with platforms like Weight & Biases for experiment tracking and VectorDB for embedding storage is plus. • Proficiency in Python and familiarity with relevant libraries and tools. • Knowledge of APIs and cloud computing platforms (e.g., AWS, GCP), with containerization technologies (e.g., Docker) being a plus. • 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. Please don’t hesitate to get in touch if you have any questions about this role or how you can bring your unique skills to our team. Why us We are more than just a company; we are a community of like-minded individuals driven by a shared passion for creating positive change in society through AI solutions. • Purpose-Driven Mission: we are a mission-driven early stage company. If you are passionate about the transformative potential of AI and committed to ensure AI solutions that are trustworthy and responsible. • Innovation & Impact: cutting-edge AI projects that have a real impact on people’s lives. • Collaborative Culture: Our team is distributed across different countries, fostering a collaborative and inclusive culture where everyone’s input is valued. We make sure to meet several times a year to work together in a place in the world defined in advance. • Remote work: We are a 100% remote team, distributed around the world. Since we do not have offices in all locations we partner with an Employer of Record. We are committed to building a diverse and inclusive team. We encourage applications from individuals of all backgrounds, beliefs, and identities. Compensation, Benefits and Perks • Premium package featuring core benefits tailored to your country of residence encompassing essential services such as health insurance and retirement plans (check our comprehensive list of core benefits per location) • 25 days 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:mozilla.ai
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Level of experience (years):Senior (5+ years of experience)
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.
