6 of 6 Linear Algebra Jobs

conversational agents. Dive into the world of traditional NLP techniques and stay ahead of the curve. Apply a strong understanding of fundamental concepts-statistics, linear algebra, calculus, regression, classification, and time series analysis - to extract valuable insights from data. Be the driving force behind our data visualisation efforts … libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series analysis ...

matrix operations and numerical solvers Profiling and optimizing GPU execution using NVIDIA tooling (e.g., qdss , Nsight Systems/Compute) Working with large-scale matrix algebra , linear equation solving, iterative solvers, and sparse/dense matrix handling Adapting existing CPU-based simulation code to GPU environments Ensuring numerical stability … Optional: contribution to Jetson-based environments if needed Required Skills Strong experience in CUDA development (custom kernels, memory management, warp optimization) Background in numerical linear algebra , matrix operations, and solving systems of equations Experience with GPU-accelerated libraries such as: cuBLAS, cuSOLVER, cuSPARSE, Thrust , or similar Knowledge ...

with TensorFlow or PyTorch; familiarity with data pipelines (e.g., Spark) is a plus. • Solid foundations in mathematics and algorithm design (probability, statistics, optimization, linear algebra). • English is the working language; additional languages are a plus. We Offer • Very competitive salary package and comprehensive benefits. • Remote-first working ...

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

design or mathematically analyse novel algorithms beyond standard machine learning approaches. Experience with invariance, stability, perturbation analysis, or noise modelling. Solid mathematical background (linear algebra, spectral methods, applied maths). Comfortable running structured experiments with multiple LLMs (Qwen models especially welcome). Proficiency in Python (NumPy, SciPy, PyTorch ...

math, quantitative finance, or other quantitative fields with a strong foundation in statistics Demonstrated proficiency in Python Strong command of foundations of applied statistics, linear algebra, and time series models Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources Knowledge of financial markets Highly ...