1 to 25 of 53 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 ...

Prototype, architect, and code robust gameplay and animation features, ensuring clean memory management, low CPU overhead, and highly modular logic. Math-Driven Animation: Utilize linear algebra and 3D mathematics to implement advanced procedural, kinematic, or dynamic character behaviors. Estimation & Scoping: Support production planning cycles by providing highly accurate … Engine ecosystem. Advanced C++ & Mathematics: High-level proficiency in modern C++, object-oriented (OO) design principles, and a strong foundational mastery of 3D math, linear algebra, and coordinate spaces. GAS Expertise: Practical, production-tested experience utilizing and extending Unreal Engine’s Gameplay Ability System (GAS). Engine Foundations ...

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 ...

experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit‐learn. Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus. Collaborative, humble and enthusiastic attitude. Preferred Qualifications, Capabilities and Skills Experience deploying on AWS cloud infrastructure using Lambda, Glue ...

/IP DNS NAT TLS/HTTPS Routing Load balancing Firewalls Congestion control Mathematics for Computing Logic Discrete maths Probability Statistics Graph theory Linear algebra Boolean algebra Combinatorics Proofs Number theory Distributed & Cloud Systems Replication Partitioning CAP theorem Event-driven architecture Idempotency Eventual consistency Queues & streams Serverless ...

/or Google ADK. Strong Python and SQL; able to write clean, production-ready code. Strong AI/ML fundamentals, including statistics, probability, linear algebra, and model evaluation. Experience with scikit-learn and either PyTorch or TensorFlow. Practical DevOps mindset: testing, CI/CD, reproducibility, code quality ...

Python are fundamental, alongside proficiency with ML frameworks like TensorFlow and PyTorch. Machine Learning Engineers need solid mathematics and statistics knowledge, particularly in linear algebra, calculus, and probability theory. Experience with cloud platforms (AWS, GCP, Azure) is essential for deploying models at scale. Skills in data preprocessing, feature ...

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 ...

data pipelines and ETL processes, directly contributing to the team's delivery of secure and stable data architectures Applies advanced data modeling techniques, including linear algebra, statistics, and geometrical algorithms to solve real world business challenges and drive actionable insights Collaborates closely with cross-functional teams to integrate ...

with natural language processing technology, including LLMs and prompt engineering is a plus Strong quantitative skills with demonstrated understanding of mathematics, probability, statistics and linear algebra Nuanced understanding of economic and financial concepts and demonstrated intuition around applying these concepts in a quantitative environment Ability to work independently ...

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 ...

takes to move from concept to production A strong mathematical background; Good candidates will be excited about things like optimisation theory, regularisation techniques, linear algebra and the like A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with ...

cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions. Strong knowledge in at least a few of the following areas: statistics, machine learning, linear algebra, optimisation. A strong product mindset with the ability to operate autonomously while working in a cross-functional and cross-team environment. Good ...

trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database ...

trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database ...

with experience in either computer vision, foundation models, or 3D medical imaging. Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation. Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases. ...

with experience in either computer vision, foundation models, or 3D medical imaging. Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation. Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases. ...

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 ...

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 ...

apply. Essential Strong academic background in mathematics, physics, engineering or a related discipline (BSc, MSc or PhD). Good understanding of statistics, linear algebra, probability, optimisation and machine learning techniques. Experience developing algorithms, numerical methods or physical simulations. Proficiency in at least one programming language used for scientific ...

risk with good understanding of risk modelling. Credit experience is preferred. Very good grasp and understanding of mathematical concepts like probability, statistics, stochastic calculus, linear algebra, Monte Carlo techniques. MSC in a related discipline Good knowledge of Python, SQL, Matlab, VBA. Good understating of financial products (Bonds, Derivatives ...

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 ...

/C++. Familiarly with data science toolkits, such as scikit-learn, Pandas Strong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniques Collaborative mindset with strong independent research abilities Commitment to the highest ethical standards #J-18808-Ljbffr ...

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. ...