1 to 25 of 42 Linear Algebra Jobs in London

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 linear algebra (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, linear algebra, 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, linear algebra, 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, linear algebra, 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 linear algebra, 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 ❯

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 linear algebra, 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 ❯

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 (linear algebra, 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 (linear algebra, 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 ❯

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 Linear Algebra 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 ❯

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 (linear algebra, 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 ❯

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 (linear algebra, 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 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, linear algebra 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 ❯

LIDAR. Experience with sensor characterisation and modelling. Familiarity with classical and contemporary approaches for state estimation and tracking (e.g. Kalman Filter, UKF, Particle Filter). Sensor calibration. Background in linear algebra and probability/stochastic processes. Familiarity with non-linear optimisation frameworks like Ceres, g2o, GTSAM, etc. Probabilistic inference and Bayesian likelihood estimation (e.g., Markov Chain Monte More ❯

of Python and modern ML libraries like PyTorch, Tensorflow, or JAX. Ability to implement models from academic papers like ICML, ICLR, NeurIPS, etc. Strong quantitative intuition and mastery of linear algebra, probability and statistics. Solid knowledge of basic data structures (list, vector, stack, heap), basic algorithms (sort, search, etc.) and associated time/memory asymptotic complexity. Maybe you More ❯

publications, or contributions to machine learning codebases. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas Strong knowledge of linear algebra, calculus and statistics Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics) Experience working with biological or chemical data and biological or chemistry software More ❯

experience in a technical field. A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation. Strong knowledge of linear algebra, calculus and statistics. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas. A passion for applying ML More ❯

Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Mathematics skills to support the above: calculus, probability theory and linear algebra. Desirable Experience in one or more of: distributed computing, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other More ❯

investment pipeline. What we're looking for: Background in Mathematics, Computer Science, Physics, or Engineering. PhD or Master’s degree from a high-ranking university. Required Mathematical skills: Advanced linear algebra, optimisation theory, statistics (including time series and high-dimensional data), machine learning, and signal processing. Required programming skills: Proficiency in modern Python and its numerical, statistical, and More ❯

experience in a technical field. A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation. Strong knowledge of linear algebra, calculus and statistics. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas. A passion for applying ML More ❯

publications, or contributions to machine learning codebases. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas Strong knowledge of linear algebra, calculus and statistics Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics) Experience working with biological or chemical data and biological or chemistry software More ❯

previously built and maintained training and inference infrastructure A robust understanding of what it takes to move from concept to production Strong experience in model training & mathematical concepts, e.g. linear algebra, greek alphabet, choice of loss functions, regularization techniques, model architecture, optimizer, learning rate schedules, etc. Thorough understanding of Python tools and libraries, keen to offer advice on More ❯

ML techniques and infrastructure Experience building and maintaining training and inference infrastructure Understanding of moving models from concept to production Strong experience in model training and mathematical concepts, e.g., linear algebra, choice of loss functions, regularization techniques, model architecture, optimizer, learning rate schedules Thorough understanding of Python tools and libraries, with the ability to advise on best practices More ❯