**Company: Symbolica AI Job Description Summary: Job Title: Machine Learning Scientist – AUS – Categorical Deep Learning
Location: Melbourne (preferred) or AUS remote
Responsibilities include helping develop pioneering research projects in categorical deep learning, working with category theorists and ML researchers, staying at the forefront of experimental advances in deep learning, and validating hypotheses through training and evaluating deep learning models. Preferred qualifications include a PhD in Computer Science or Mathematics, a track record of research published in top-tier conferences, experience with functional programming languages and deep learning frameworks, expertise in neural network architectures, and exceptional communication skills. Competitive compensation offered. Salary and equity levels dependent on experience and location. Job Description: Machine Learning Scientist – AUS – Categorical Deep Learning Remote·Full time Apply for Machine Learning Scientist – AUS – Categorical Deep Learning Collaborate with our growing team on implementing our categorical deep learning research programme Description At Symbolica, we are building deep learning models which performstructured reasoning: manipulate structured data, learn algebraic structure in it, and do so with an interpretable and verifiable logic. To that end, we are developing new mathematical foundations for deep learning:categorical deep learning . We are now assembling a R&D lab of expert category theory and machine learning researchers to develop this theory and apply it to the problems of code synthesis and theorem proving. We are committed to fundamental ideas, but also their execution in practice. As a machine learning scientist, you will help us expand and carry out our research & development program. You will work in a team on projects developing categorical…… deep… learning and experiment with novel architectures, helping us form and validate hypotheses. This is a rare opportunity to work on an innovative and transformative project, and make significant contributions to the field of artificial intelligence and applied category theory. Responsibilities: • Help the development of pioneering research projects in categorical deep learning • Work closely with category theorists and machine learning researchers, bridging the gap between state of the art research on deep learning architectures and their structural formulation in category theory • Stay at the forefront of experimental advances in deep learning, and ensure our theoretical models are grounded and coherent with respect to these advances • Help us form hypotheses, and validate them experimentally by training and evaluating deep learning models • Work simultaneously at different levels of abstraction – from understanding high-level categorical constructions to implementing low-level details of architecture in code Preferred qualifications: • PhD in Computer Science, Mathematics, or similar discipline. • Proven track record of research published in top-tier conferences (e.g. NeurIPS, ICML, ICLR, AAAI, COLT), and journals • Experience with functional programming languages (e.g. Haskell, Idris, Scala) • Practical experience with deep learning frameworks such as JAX, Pytorch, Tensorflow, etc. • Expertise in neural network architectures and a desire to work with category theory or type theory • Exceptional communication and interpersonal skills. Location: • Melbourne (preferred) or AUS remote We offer competitive compensation, including equity and health insurance. Salary and equity levels are commensurate with experience and location. #J-18808-Ljbffr Company: Symbolica Qualifications: Language requirements: Specific requirements: Educational level: Level of experience (years): Senior (5+ years of experience) Tagged as: Austria, Industry, Machine Learning, Neural Networks, NLP Company: Symbolica AI Qualifications: Language requirements: Specific requirements: Educational level: Level of experience (years): Senior (5+ years of experience) Tagged as: Austria, Industry, Machine Learning, Neural Networks, NLP
Company:Symbolica AI
Qualifications:
Language requirements:
Specific requirements:
Educational level:
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.
