career development, and pay reviews. They participate in the budget process, as well as forecasts for their department. Machine Learning Managers have extensive knowledge of the field and possess a combination of machine learning, computer science, data mining, and statistical experience. They demonstrate strong leadership skills and create … experience working with very large datasets; familiarity with parallel programming or parallel algorithms development; familiarity with machine learning concepts, data mining, knowledgediscovery, and information retrieval (NLP & Semantic Analysis); strong background in Math, Statistics, and Engineering concepts; demonstrated leadership attributes. Optimal Qualifications: Masters or PhD in Computer … experience working with very large datasets; experience with parallel programming or parallel algorithms development; experience with machine learning concepts, data mining, knowledgediscovery, and information retrieval (NLP & Semantic Analysis); strong background in Math, Statistics, and Engineering concepts; experience with Graph Analysis, Recommender Systems (Collaborative Filtering), and probabilistic More ❯
access. AI & GenAI Integration: Embed Large Language Models (LLMs) and Large Multimodal Models (LMMs) into business workflows, enabling practical applications such as classification, knowledgeextraction, and recommendation engines. Continuous Improvement: Stay updated on emerging cloud technologies, MLOps practices, and generative AI advancements to continually enhance infrastructure and capability. More ❯
As AI agents become the norm in this industry, so does the need for efficient legal information retrieval, semantic search capabilities, and structured knowledge representation. Your work will bridge the gap between advanced search technologies and the complex information needs of the legal domain, making legal knowledge more accessible, navigable, and actionable. Responsibilities: Develop and advance knowledgeextraction and representation methods, particularly in: Structured knowledgeextraction from legal texts and images Knowledge graphs/ontology engineering Legal knowledge base construction Specialised embedding methods for multimodal content in … the legal domain Develop methods for retrieval and reasoning over legal knowledge bases and systems (e.g., hybrid search approaches combining symbolic and neural techniques, query understanding and rewriting for legal search) Perform fine-tuning and reinforcement learning to teach language models how to interact with new information architectures. More ❯
to architect novel approaches that leverage the complementary strengths of these technologies. This involves designing systems where LLMs can effectively communicate with our knowledge graph infrastructure, translating natural language into structured symbolic representations and vice versa. A significant part of your role will focus on extending our platform … s capabilities by developing algorithms and solutions that manage the interaction between different AI paradigms. This includes creating mechanisms for knowledgeextraction and transfer between LLMs and symbolic systems. You'll design and implement neurosymbolic architectures that preserve the interpretability advantages of symbolic AI while incorporating the flexibility … innovation around our core platform. You'll explore emerging technologies and methodologies that could enhance Rainbird's capabilities in areas such as automated knowledge acquisition, reasoning transparency, and computational efficiency. This requires staying current with academic research and industry developments to identify opportunities for platform evolution. The role More ❯
of your work Working closely within a multidisciplinary team of engineers, product managers and analysts, whilst enabling and empowering the wider team through knowledge sharing and strong documentation Partnering with the product manager to create our product strategy for a particular product Applying best practices to our style … of considerations behind your work and knowing how to engage stakeholders at all levels, in particular by designing and running workshops to facilitate knowledgeextraction and collaborative ideation A collaborative working style, strong interpersonal skills, and the ability to work closely with engineers, analysts, and senior stakeholders - both More ❯
