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 ❯
You Have Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field, with expertise in calibration, localization, and/or 3D mapping Strong mathematical foundation in linearalgebra, probability theory, numerical optimization, 3D geometry, Lie theory, and 3D kinematics Strong theoretical understanding and practical experience with different linear and non-linear state estimation More ❯
fields preferred. Minimum 2 years relevant work experience preferred. Excellent programming skills in Python. Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). 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 ❯
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 ❯
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 ❯
about quality of experience over quantity. Programming Skills: Preferably extensive Python experience. Problem-Solving & Math: Outstanding problem-solving skills, with a creative and analytical mindset. Strong foundation in mathematics (linearalgebra, calculus, probability) and comfort with reading research papers when needed. Communication & Collaboration: Excellent communication skills. You can clearly articulate complex technical concepts to team members and actively More ❯
of relevant experience Master's or Ph.D. degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field relevant to machine learning, or equivalent experience Strong background in LinearAlgebra, Probability, Signal Processing, and machine learning concepts Proficient programming skills in languages such as C/C++, Python, and others Preferred Qualifications Experience in development related to More ❯
security tactics. Post graduate degree and/or related certifications in Machine Learning or Artificial Intelligence. PhD or masters in AI/ML preferred. Strong understanding of probability theory, linearalgebra and calculus. Knowledge of current academic work in Adversarial attacks of LLMs. In-depth experience with exploiting OWASP LLM Top 10 application vulnerabilities, such as prompt injection More ❯
Finance, Ads, or others). Production experience with Deep Learning models (training, fine-tuning, or deployment). Excellent software engineering skills in Python or C++. Strong analytical skills in linearalgebra, geometry, and probability. Experience with a deep learning framework, such as PyTorch, JAX, TensorFlow. Extra Credit Relevant industry experience with low-latency systems (prior work on self More ❯
Kubernetes containers - Statically-typed tabular data storage engine - Reactive Python-based web application framework for data analysis and visualization Here are some hard technical requirements: - Strong foundation in statistics, linearalgebra, and algorithmic reasoning, with an understanding of the methods underlying bioinformatics tools and LLMs. - Understanding of mechanics of wet lab biology, either from direct experience or interfacing More ❯