1 to 25 of 39 Permanent Linear Algebra Jobs

with the CEO/CTO to formalise the platform's theoretical basis, review quantitative approaches, and co-author peer-reviewed papers. Deep fluency in linear algebra, vector spaces, statistics, probability, and AI is central to the role. This is a fractional advisory engagement at approximately 30% FTE, with … flexibility on scheduling. Key Responsibilities Provide mathematical and theoretical guidance on the core platform architecture — with a strong focus on linear algebra, vector spaces, metric spaces, and multi-dimensional decision frameworks. Co-author and review peer-reviewed research papers targeting top AI, ML, and fairness venues. Advise ...

improve large-scale modelling and simulation applications. Investigate new HPC technologies, GPU architectures and computational approaches. Apply mathematical techniques, including numerical methods and linear algebra, to scientific computing challenges. Improve software performance, scalability and computational efficiency. Collaborate with researchers, computational scientists and software engineers to deliver innovative solutions. … with C++ or another compiled language, ideally alongside Python. Experience developing computationally intensive, numerical or scientific software. Good understanding of mathematical modelling, numerical methods, linear algebra or scientific algorithms. Experience working with HPC systems, parallel computing or large-scale computational environments. Strong working knowledge of Linux/UNIX ...

someone who can independently investigate complex problems, work effectively in an established codebase, and grow into broader technical leadership over time. Experience in linear algebra and/orLagrangiananalysis is highly desirable.Programming ability isrequired, but prior C++ experience is not essential.The ideal candidate will have both postgraduate/research … debuggers, performanceprofilersand memory profilers. Experience with source control systems and continuous integration/continuous developmenti.e.git and Azure DevOps. Background in one or both of: Linear algebra Lagrangiananalysis Problem solving– able to break down difficult technical and mathematical problems and develop practical, effective solutions. Critical thinking– evaluates evidence objectively ...

relational and non-relational databases Experience with AWS cloud services (S3, Lambda, EC2, RDS, Glue, or similar) Strong applied mathematics – statistics, probability, linear algebra, or signal processing Demonstrated ability to read, understand, and extend complex algorithms and dense business logic written by others Understanding of software engineering principles ...

software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design) Demonstrated mathematical maturity — comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability Deep proficiency in Python; experience with R and/or C/C++ is a strong plus Extensive experience ...

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. ...

tuning, RL, RLHF), and optimization methods A results‐oriented track record of having taken ML ideas from theory to measurable impact Strong math fundamentals (linear algebra, probability, optimization) and mastery of regression/ML for large scale data Hands‐on with modern machine learning (sequence models/transformers ...

data sampling methods. Ability to apply statistical analysis techniques to analyze financial data. Mathematics and Machine Learning : Solid foundation in mathematical principles, including linear algebra and calculus, with a focus on regression analysis. Exposure to machine learning and deep learning algorithms and methods in the presence of sparse ...

build and make predictions with those models Strong understanding of machine learning approaches and algorithms Deep understanding of Statistical/Probabilistic programming and Linear Algebra Be an expert in (Python, R, SQL) programming for Data Science and Time Series analysis Have in depth understanding of statistical modelling/ ...

Python Stack, SQL) to manipulate data and draw insights from large data sets The capability to perform statistical analysis, quantitative analysis, multivariate calculus and linear algebra Proficient experience deploying ML implementations in an enterprise setting Proven skills with Text Analytics, NLP and intelligent document processing (IDP) for modelling ...

Experience using AI/ML frameworks and libraries including TensorFlow, PyTorch, Keras, Pandas, Matplotlib and Scikit-learn. Knowledge of mathematics including calculus, probability, statistics, linear algebra and optimisation. Strong computer science fundamentals including algorithms, data structures and parallel/distributed computing. Programming experience in one or more languages ...

expect in the hiring process A preliminary phone call with the recruiter A coding exercise on HackerRank - covering core data science theory (math, statistics, linear algebra) and Python fundamentals (data structures & algorithms). A take-home assignment A technical interview with a Lead in our Data Science Team ...

conventional image processing algorithms, supported by a sound understanding of imaging fundamentals, noise, sampling, resolution and calibration. Strong mathematical and analytical skills, including statistics, linear algebra, numerical methods and optimisation. Experience preparing datasets, designing experiments, selecting evaluation metrics and diagnosing overfitting, data leakage and generalisation problems. An understanding ...

Advanced ML & deep learning: deep theoretical and practical grasp of modern frameworks (PyTorch preferred), optimisation, and neural-network primitives. Scientific computing & math: strong linear algebra, calculus, probability, and statistics; fluency with NumPy, SciPy, and Pandas. Research translation: read an academic paper, understand its mechanics, and reproduce or adapt ...

such as publications, a thesis, open-source work or applied research where you owned the original contribution Solid mathematical foundations in statistics, probability and linear algebra Strong Python and PyTorch skills, and experience running experiments end-to-end A genuine interest in data-centric AI: curation, evaluation ...

systems Solid foundation in computer vision, machine learning, and statistical signal processing Solid math background with deep understanding of 3D geometry, probability, statistics, and linear algebra Ability to transform ideas into clean, fast and reliable code Attention to detail, strong desire for quality and good communication skills Minimum ...

training and serving benchmarks that are representative of Google production, industry, and the ML community, using them to identify performance opportunities, drive Accelerated Linear Algebra (XLA) Graphics Processing Unit (GPU)/Triton performance, and guide XLA releases. Engage with Google product teams like DeepMind to solve their ...

problems. Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred). Deep understanding of probability, statistics, uncertainty, linear algebra and calculus. Extensive experience working with large datasets, data preparation and machine learning workflows. Proven experience applying classification, clustering, dimension reduction ...

Azure Service Bus, and Azure Event Hubs.Experience in containerising models and deploying in Kubernetes.Have experience implementing algorithms and data-structures.Have a good knowledge of linear algebra, calculus, and discrete mathematics.After you submit your application, you will receive an email from Shell providing a link to an online assessment ...

financial institutions, including global investment banks and multi-strategy hedge funds. Who will love this job A scientist – you are comfortable with numerical methods, linear algebra, partial differential equations, probability theory and statistics An engineer – who has a passion for computer science, system performance, clean code and architecture ...

financial institutions, including global investment banks and multi-strategy hedge funds. Who will love this job A scientist – you are comfortable with numerical methods, linear algebra, partial differential equations, probability theory and statistics An engineer – who has a passion for computer science, system performance, clean code and architecture ...

Math/Data Science from a top-tier university (MIPT, HSE, MSU, SPbSU, ITMO, YSDA, or international equivalents). Strong foundation in probability, statistics, linear algebra, and algorithms. Tech Stack & Hard Skills: Python (NumPy, Numba). PyTorch or JAX (for the ML track) OR advanced backtesting/quantitative ...

Electrical Engineering, Statistics, or equivalent fields. Applied AI experience (generative AI, agentic solutions, regression and classification, supervised, and unsupervised learning). Strong mathematical background (linear algebra, calculus, probability and statistics). Experience with scalable ML (MapReduce, streaming). Ability to drive a projectand workbothindependently and in a team. ...

minimum of 2 years of commercial experience applying statistical modelling and machine learning techniques to real‐world problems. Solid grounding in probability, statistics, uncertainty, linear algebra and calculus. Experience working with large datasets, data transformation and cleaning. Experience with classification, clustering, dimension reduction and other machine learning methods. ...

enthusiastic to take on new problems across the full-stack as we continue to push technology forward. TPU team develops the Accelerated Linear Algebra (XLA) TPU parallelizing compiler used to partition, optimize, and run large-scale machine learning models across multiple TPU accelerators for internal (e.g. Google DeepMind ...