
Machine Learning
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning expert with a PhD in ML/AI or related fields, offering a contract length of "X months" at a pay rate of "$X/hour". Key skills include proficiency in Python, deep learning, and experience publishing in top-tier conferences.
π - Country
United Kingdom
π± - Currency
Β£ GBP
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π° - Day rate
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ποΈ - Date discovered
August 23, 2025
π - Project duration
Unknown
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ποΈ - Location type
Unknown
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Staines-upon-Thames
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π§ - Skills detailed
#AI (Artificial Intelligence) #Distributed Computing #Programming #Debugging #PyTorch #Mathematics #Libraries #Calculus #Python #Visualization #Deep Learning #C++ #ML (Machine Learning) #Statistics #NumPy #Documentation #Java #Computer Science #Linux #Model Optimization
Role description
Role and Responsibilities
As a forward-thinking company at the forefront of innovation, we seek an individual passionate about pushing the boundaries of AI:
β’ Conduct cutting-edge research to develop state-of-the-art solutions or propose novel research challenges based on real-world case studies in AI.
β’ Develop high-quality code with detailed documentation to support reproducible research in local and international AI communities.
β’ Review state-of-the-art research papers and develop prototype solutions.
β’ Publish findings in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, EMNLP, CVPR, ICCV, ECCV, AAAI, ACL, IEEE TPAMI, IEEE TNNLS, IJCV, and JMLR.
Skills and Qualifications
β’ Pursuing or completed PhD in ML/AI, Computer Science/Engineering, or related disciplines.
β’ Proficiency in mathematics (calculus, probability, statistics, linear algebra, optimization) and computer science (algorithms, data structures, parallel/distributed computing).
β’ Strong fundamentals in Machine Learning, Computer Vision, and Deep Learning.
β’ Hands-on experience in areas such as Generative AI, Foundation Models, Parameter-Efficient Fine-Tuning (PEFT), Data/Model Privacy, or Model Optimization for Multi-Task Learning.
β’ First-author publications in top ML/AI conferences/journals (e.g., ICML, NeurIPS, ICLR, CVPR, ECCV, IEEE TPAMI, AAAI).
β’ Experience in Linux environments.
β’ Proficiency in programming languages such as Python, Java, or C++.
β’ Experience with machine learning libraries like PyTorch, SciKit, NumPy, etc.
β’ Excellent communication skills, teamwork abilities, and a results-oriented attitude.
β’ Strong problem-solving and debugging skills.
Desirable Skills:
β’ Expertise in Image/Video generation, PEFT-LoRA, Diffusion/Autoregressive Models.
β’ Experience in Knowledge Distillation.
β’ Experience in computer graphics and rendering for visualization.
Role and Responsibilities
As a forward-thinking company at the forefront of innovation, we seek an individual passionate about pushing the boundaries of AI:
β’ Conduct cutting-edge research to develop state-of-the-art solutions or propose novel research challenges based on real-world case studies in AI.
β’ Develop high-quality code with detailed documentation to support reproducible research in local and international AI communities.
β’ Review state-of-the-art research papers and develop prototype solutions.
β’ Publish findings in top-tier conferences and journals, such as NeurIPS, ICML, ICLR, EMNLP, CVPR, ICCV, ECCV, AAAI, ACL, IEEE TPAMI, IEEE TNNLS, IJCV, and JMLR.
Skills and Qualifications
β’ Pursuing or completed PhD in ML/AI, Computer Science/Engineering, or related disciplines.
β’ Proficiency in mathematics (calculus, probability, statistics, linear algebra, optimization) and computer science (algorithms, data structures, parallel/distributed computing).
β’ Strong fundamentals in Machine Learning, Computer Vision, and Deep Learning.
β’ Hands-on experience in areas such as Generative AI, Foundation Models, Parameter-Efficient Fine-Tuning (PEFT), Data/Model Privacy, or Model Optimization for Multi-Task Learning.
β’ First-author publications in top ML/AI conferences/journals (e.g., ICML, NeurIPS, ICLR, CVPR, ECCV, IEEE TPAMI, AAAI).
β’ Experience in Linux environments.
β’ Proficiency in programming languages such as Python, Java, or C++.
β’ Experience with machine learning libraries like PyTorch, SciKit, NumPy, etc.
β’ Excellent communication skills, teamwork abilities, and a results-oriented attitude.
β’ Strong problem-solving and debugging skills.
Desirable Skills:
β’ Expertise in Image/Video generation, PEFT-LoRA, Diffusion/Autoregressive Models.
β’ Experience in Knowledge Distillation.
β’ Experience in computer graphics and rendering for visualization.