- Develop an independent research program focused on new tools and techniques for probabilistic models, Bayesian optimization, and related fields
- Collaborate with research teams to meet research goals
- Report research findings internally and externally
- Contribute to internal product development and customer research projects
- Apply cutting-edge machine learning research to real-world problems
- Participate in developing open source libraries such as Trieste, GPflow, and GPflux
- Develop theoretically rigorous and scalable algorithms
- Publish papers at leading machine learning conferences
Requirements
- A PhD in a technical field or an equivalent level of experience
- Published work in machine learning, statistics, or optimization conferences and/or journals
- Background in decision making, including Bayesian optimization, bandits, reinforcement learning, or active learning (advantage)
- Background in probabilistic modelling and methods, including Gaussian processes, Bayesian neural networks, or variational inference (advantage)
- Experience in numerical programming with Python, NumPy, TensorFlow, or PyTorch (advantage)
- Experience or interest in applying machine learning to solve real-world problems (advantage)
- Willingness to work as part of a team, review documents and code, and provide constructive feedback
- Passion for continuously developing machine learning and research skills and helping others improve theirs
- Applicants may range from fresh PhD graduates to experienced team leads
Core Competencies
Demonstrates expertise in developing probabilistic models and Bayesian optimization techniques, with a strong background in machine learning applications and research publication. Capable of collaborating effectively within research teams and contributing to open source projects while applying advanced algorithms to real-world challenges.
Highest-signal resume keywords
- PhD In A Technical Field
- Published Work In Machine Learning
- Bayesian Optimization
- Numerical Programming With Python
- Experience With TensorFlow Or PyTorch
ATS Optimization Keywords
Hard Skills
- Probabilistic Modelling
- Bayesian Neural Networks
- Gaussian Processes
- Variational Inference
- Reinforcement Learning
- Active Learning
- Scalable Algorithms
- Machine Learning Research
- Statistical Analysis
- Algorithm Development
Soft Skills
- Team Collaboration
- Constructive Feedback
- Passion For Learning
Industry Keywords
- Machine Learning
- Optimization
- Research Publication
- Decision Making
- Open Source Development
Tools & Technologies
- NumPy
- TensorFlow
- PyTorch
- Trieste
- GPflow
- GPflux
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Machine Learning Researcher in Cambridge employer: Jobtailor
As a Client Services Coordinator at our dynamic company, you will thrive in a supportive work culture that prioritises employee growth and development. We offer comprehensive training, opportunities for advancement, and a collaborative environment where your contributions are valued. Located in a vibrant area, our team enjoys a healthy work-life balance and the chance to engage with diverse clients, making every day rewarding and meaningful.
