**Company: Deimos Space UK Job Description Summary: DEIMOS is looking for a Machine Learning Engineer to join their Computer Vision/Artificial Intelligence Competence Centre focusing on onboard processing applications in Space. The role involves developing and deploying machine learning projects, collaborating with team members and clients, and implementing MLOps infrastructure. Requirements include a Master’s or Ph.D. in related fields, experience in deploying ML systems, and proficiency in programming languages like Python and frameworks like TensorFlow. Experience in aerospace-related projects, MLOps solutions, Linux systems, and cloud infrastructure is highly desirable. Good level of English and personal skills such as teamwork, organization, and communication are also required. Level of experience required is Senior (5+ years of experience). Job Description: Machine Learning Engineer DEIMOS is looking for an engineer to join the Computer Vision/Artificial Intelligence (CV/AI) Competence Centre of the Avionics Business Unit, Flight Systems Directorate. This role focuses on supporting Deimos’ AI/CV flight systems team in researching, developing, deploying and scaling our computer vision portfolio for onboard processing applications in Space. You will work on Machine Learning projects and products throughout their lifecycle – from early-phase R&D activities to productization and deployment. The work of the AI/CV Competence Centre is oriented to the design, development, specification, and validation of Computer Vision solutions for embedded flight segment applications, including real-time advanced onboard data processing and intelligent decision making. This preferred locations for this role are either Harwell, UK, or Madrid, Spain, although other Deimos sites may also be considered. Duties: The main responsibilities are: • Research… design, implement, and deploy machine learning models and algorithms that address specific challenges and opportunities related to on-board processing in Space. • Collaborate with team-members and clients across Europe to understand project requirements, objectives, and constraints. • Process and analyse datasets to extract meaningful insights and features for model development. • Design, implement and maintain industry-standard MLOps infrastructure for new and existing ML products • Optimize and standardize ML training and validation processes, data warehousing and pipelines. Education: Master’s or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field. Professional Experience: The position will be tailored to the level of experience; practical industry experience deploying and maintaining ML systems in production would be viewed very positively. Technical Requirements: Required: • Strong foundation in machine learning algorithms, statistics, and data structures within relevant technical projects. • Proficiency in programming languages, frameworks, and tools, such as Python, TensorFlow, PyTorch. • Experience with data preprocessing, feature engineering, and model evaluation techniques. Highly Desirable: • Experience working on aerospace-related projects • Experience deploying MLOps solutions and working within CI/CD frameworks • Experience with Linux systems and cloud infrastructure (AWS, Azure, etc.) • Experience developing embedded ML applications (C++, CUDA, TensorRT) Language Skills: Good level of English, spoken and written Personal Skills: • Capability to integrate in and work within a trans-European team • Solid organisational, analytical and reporting skills • Autonomy and willingness to take initiative • Excellent communication skills • Energetic, positive team player mentality Ref.: HRRECRUIT-794
Company:Deimos Space UK
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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.
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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.
