1 to 25 of 44 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 ...

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 ...

frameworks and libraries: scikit-learn, TensorFlow, or PyTorch. Statistics & Math: Strong foundation in statistical modeling, probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases & Querying: Proficiency in SQL for extracting, manipulating, and preparing data from relational databases. Experience with NoSQL databases ...

libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model mechanics. Databases & Querying: Proficiency in SQL for extracting, manipulating, and preparing data from relational databases. Experience with NoSQL databases ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...

Explain the mechanics and rationale behind core algorithms, gradient descent, backpropagation, attention mechanisms, regularisation techniques Understand the mathematical foundations underpinning these concepts, including linear algebra, calculus, and probability theory Reason about model behaviour from first principles during analysis and debugging Read research papers and implement key concepts independently ...