transformer architectures to create intelligent conversational agents. Dive into the world of traditional NLP techniques and stay ahead of the curve. Apply a strong understanding of fundamental concepts-statistics, linearalgebra, calculus, regression, classification, and time series analysis - to extract valuable insights from data. Be the driving force behind our data visualisation efforts - whether its Tableau, Power BI … python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linearalgebra principles for modelling and optimisation. Calculus for optimising algorithms and models. Predictive modelling techniques for regression and classification. Time series analysis for handling time-dependant data. Deep More ❯
high-performance CUDA kernels for 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 and precision in GPU-accelerated … handover of GPU-optimized modules Optional: contribution to Jetson-based environments if needed Required Skills Strong experience in CUDA development (custom kernels, memory management, warp optimization) Background in numerical linearalgebra , matrix operations, and solving systems of equations Experience with GPU-accelerated libraries such as: cuBLAS, cuSOLVER, cuSPARSE, Thrust , or similar Knowledge of NVIDIA debugging/profiling tools More ❯
small-scale system and process improvements to enhance functionality and efficiency. Qualifications Preferred: Applied Machine Learning experience (regression, classification, supervised, and unsupervised learning ) with a strong mathematical foundation in linearalgebra , calculus , probability, and statistics. Experience in time-series data analysis , including cleansing and normalization , and experience with scalable Machine Learning ( MapReduce , streaming). Software development expertise in More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Forward Role
to-day, you'll: ? Deliver engaging teaching sessions covering the full ML lifecycle — data prep, model training, evaluation, deployment and monitoring at scale. ? Explain the maths behind ML models (linearalgebra, calculus, probability, stats) in an accessible, engaging way. ? Support learners throughout their apprenticeship journey alongside Learner Success Coaches. ? Contribute to content and product development — creating learning materials More ❯
platforms. Data structures and design/analysis of algorithms. Analysis of concurrency and parallelism for speed/space performance tradeoffs. Bonus Experience Exchange traded financial instruments. Statistics, discrete mathematics, linear algebra. Problem-solving and proof construction. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at California residents More ❯
how to build maintainable systems. 5+ years coding in an object-oriented language - Java is our main one, but others are fine too. Strong grasp of math and kinematics - linearalgebra, rotation matrices, transformations. Real experience programming and working with industrial robots (ABB, KUKA, etc.). You've set up robots in simulation environments like ABB RobotStudio or More ❯