AI models, code, and processes to ensure efficient collaboration and reproducibility. Preferred Skills: Experience with NLP (Natural Language Processing), computer vision, or reinforcement learning. Mathematics & Algorithms: Strong knowledge of linearalgebra, probability, statistics, and optimization techniques. Knowledge of MLOps, CI/CD pipelines, and automated testing for machine learning models. Version Control: Familiarity with version control tools such More ❯
Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linearalgebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication More ❯
London, England, United Kingdom Hybrid / WFH Options
Made Tech Limited
some blog posts about your discipline, or perhaps even delivered a talk or two that you’d like to share. Skills, Knowledge and Expertise Technical skills Good understanding of linearalgebra (vectors, matrices, tensors etc.) and statistics (probability distributions, probability, bayesian stats etc.) Good working knowledge of Python Implementing end-to-end ML pipelines Hand-on experience in More ❯
Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linearalgebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication More ❯
Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linearalgebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication More ❯
Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linearalgebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication More ❯
experience), or equivalent experience Track record of delivery of outstanding research using deep learning techniques, including designing new ML architectures, hands-on experimentation, analysis, and visualisation Strong knowledge of linearalgebra, calculus, probability, and statistics Demonstrated ability to write clean, idiomatic, and highly performant Python code Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific More ❯
quantitative researcher, quantitative analyst or another relevant role Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linearalgebra, and numerical methods Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models More ❯
a data scientist, quantitative researcher, or similar role. Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology, or Engineering. Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linearalgebra, and numerical methods. Experience with models like regression, tree-based models, support vector machines, PCA, clustering, matrix factorization, deep learning, etc. Proficiency in Python and its machine More ❯
London, England, United Kingdom Hybrid / WFH Options
myGwork - LGBTQ+ Business Community
experience), or equivalent experience Track record of delivery of outstanding research using deep learning techniques, including designing new ML architectures, hands-on experimentation, analysis, and visualisation Strong knowledge of linearalgebra, calculus, probability, and statistics Demonstrated ability to write clean, idiomatic, and highly performant Python code Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific More ❯
in AI engineering, machine learning, or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to More ❯
in AI engineering, machine learning, or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to More ❯
in AI engineering, machine learning, or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to More ❯
data scientist, quantitative researcher, quantitative analyst or another relevant roleDegree in Applied Mathematics, Computer Science, Financial Engineering, Technology or EngineeringKnowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linearalgebra, and numerical methodsExperience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models (e.g. More ❯
video security use cases, and convert those ideas to working code. Requirements You should be a good software engineer who enjoys writing production-grade software. Strong machine learning fundamentals (linearalgebra, probability and statistics, supervised and self-supervised learning) Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in More ❯
video security use cases, and convert those ideas to working code. Requirements You should be a good software engineer who enjoys writing production-grade software. Strong machine learning fundamentals (linearalgebra, probability and statistics, supervised and self-supervised learning) Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in More ❯
Experience working in hybrid team structures, collaborating with contractors and external partners. Qualifications: A degree in a quantitative field (STEM Bachelor's/Master's) with strong foundations in LinearAlgebra, Calculus, and Statistics, plus 2+ years as a Data Scientist. Alternatively, substantial industry experience combined with recognised certifications in Data Science demonstrating hands-on implementation. Why Join More ❯
London, England, United Kingdom Hybrid / WFH Options
GSK Group of Companies
build and make predictions with those models Strong understanding of machine learning approaches and algorithms (e.g. LSTM, Markov-Chain Models etc) Advanced understanding of Statistical/Probabilistic programming and LinearAlgebra Be proficient in (Python, SQL) programming for Data Science and Time Series analysis Have in depth understanding of statistical modelling/ML techniques for time series forecasting More ❯
and evaluation. Ability to perform ad-hoc data mining and integrate large structured and unstructured datasets from multiple sources. Strong knowledge of statistics and probability; a foundation in calculus, linearalgebra, and analysis is advantageous. Package Our client values autonomy and flexibility. Benefits include: Company pension scheme 25 days holiday per year Flexible working locations (home, client site More ❯
Engineering, Statistics, or equivalent fields. Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). Experience with prototyping languages such as Python and R. Strong mathematical background (linearalgebra, calculus, probability and statistics). Experience with scalable ML (MapReduce, streaming). Ability to drive a project and work both independently and in a team. Smart, motivated More ❯
and translating research into practical solutions for predictive analytics. Experience in solution design, architecting and outlining data analytics pipelines and flows. Advanced Mathematics skills including experience with Bayesian statistics, linearalgebra and MVT calculus, advanced data modelling and algorithm design experience. Design and deployment experience using Tensor Flow, Spark ML, CNTK, Torch or Caffe. The perks A flexible More ❯
video security use cases, and convert those ideas to working code. Requirements You should be a good software engineer who enjoys writing production-grade software. Strong machine learning fundamentals (linearalgebra, probability and statistics, supervised and self-supervised learning) Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in More ❯
video security use cases, and convert those ideas to working code. Requirements You should be a good software engineer who enjoys writing production-grade software. Strong machine learning fundamentals (linearalgebra, probability and statistics, supervised and self-supervised learning) Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in More ❯
video security use cases, and convert those ideas to working code. Requirements You should be a good software engineer who enjoys writing production-grade software. Strong machine learning fundamentals (linearalgebra, probability and statistics, supervised and self-supervised learning) Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments in More ❯
experience also considered). Extensive experience in designing, training, debugging, and evaluating machine learning models using frameworks like PyTorch, TensorFlow, or JAX. Strong foundation in mathematics and statistics, including linearalgebra, probability, and optimization. Excellent scientific writing and communication skills. Preferred Qualifications Experience in computational biology, genomics, or drug discovery. Familiarity with RNA biology, structural biology, or systems More ❯