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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 linearalgebra 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 linearalgebra, 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 ❯
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 ❯
London, England, United Kingdom Hybrid / WFH Options
Isomorphic Labs
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 linearalgebra, 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 linearalgebra, 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 ❯