376 to 400 of 509 Deep Learning Jobs

logistics estimation solutions aligned with business goals, partnering with Product Management to prioritize initiatives. Cross-functional Collaboration: Manage dependencies and collaborate closely with Machine Learning and Backend Engineers for effective ETA implementation. KPI Ownership: Take ownership of logistics KPIs, specifically focusing on improving overall ETA accuracy throughout the customer … journey. Root Cause Analysis: Lead deep-dive analysis into ETA model accuracy gaps to diagnose and address operational friction points. Strategic Planning: Translate analysis findings into actionable plans and conceptual designs for new features or model improvements. Stakeholder Communication: Act as the primary interface, translating complex data ...

dashboards, alerts, and automated remediation so we catch regressions before users do. Respond to and learn from production incidents.### **Who we're looking for:*** Deep experience with GPU programming and performance work (CUDA, Triton, CUTLASS, or similar). Any other deep systems programming experience is a plus. … workloads.### **Qualifications:*** 3+ years of professional software engineering experience with meaningful work on ML inference or high-performance systems.* Familiarity with at least one deep learning framework (PyTorch, JAX, TensorFlow).* Understanding of GPU architectures (memory hierarchy, warp scheduling, tensor cores).* Understanding of common LLM architectures ...

technical skills to bring AI concepts from idea to real‐world demonstration, all while helping build AI capabilities among colleagues. Key Responsibilities Build deep technical and regulatory understanding of our cabin/seat electronic and data systems. Develop and test edge‐AI solutions that enhance passenger experience and advance … Degree (or equivalent experience) in Engineering, Computer Science, Data Science, Electronics, or similar (Essential) Proven experience designing, training, and deploying AI/ML models (deep learning/classical ML) on real‐world problems (Essential) Hands‐on skills integrating and deploying AI solutions on edge or resource‐constrained platforms ...

Cross, London. Key Responsibilities: Frontier Technical Breakthroughs Develop ViT and multimodal large model architectures with improved reasoning and efficiency Advance multimodal alignment, representation learning, and long-context modelling Explore scalable training methods for large multimodal models Optimize model architectures for generalization and performance Data Ecosystem Construction Process large-scale … above in Computer Science, Mathematics, Statistics, or related technical disciplines. Technical Skills: Proficient in Python programming with strong hands-on experience in PyTorch and deep learning frameworks. Core Competencies: Strong algorithm development and implementation skills, solid mathematical and logical reasoning ability, and excellent cross-functional communication and collaboration ...

feature or writing scripts to analyse performance bottlenecks. You're starting a journey where problems are often ambiguous, priorities shift quickly, and learning from more experienced colleagues will accelerate your growth significantly. To succeed as a Mid-Level RAD Engineer, you will be a proponent of agile principles … feedback. Self-directed learner: You take ownership of understanding the Aquis platform and trading technology. You read code, ask questions, and invest in deep learning without constant prompting. Good team player: You collaborate well across teams, take feedback constructively, and help colleagues succeed. Autonomous but seeks guidance wisely ...

member of the Embodied AI group. You will invent and develop algorithms and systems that sit at the cross-section of computer vision, machine learning, AI, graphics, and robotics. We're passionate about discovery, so we're looking for scientists who want to learn, publish, teach, and deploy every … novel models to production. Publish Your Work - Publish and present your work. What You'll Bring A PhD in computer vision, robotics, graphics, machine learning, or a related field, or equivalent research experience, with a publication record at top venues. Substantial expertise in robotics or embodied AI, including experience ...

will advance research toward a safe, medically licensed agentic system for triadic care, deployed to doctors and health systems globally. Our team blends deep learning and reinforcement learning to tackle high-impact medical challenges, with a focus on safe, scalable AI for real-world health outcomes ...

whether papers, product releases, open‐source contributions, or other artifacts. 3+ years of software engineering experience, including familiarity with Python and at least one deep learning framework. Experience using the latest coding agents, and opinions about optimal workflow. Enthusiasm for experimental organizational design. AI‐pilled: adopting agents, keen … discipline. Contribution to a well‐cited work in AI for Science writ large (e.g., ML to predict protein structure, neural weather forecasting systems, reinforcement learning for materials discovery, or causal models for financial risk prediction). Hands‐on experience using AI agents to automate parts of the scientific workflow ...

behaviour Optimisation of code running on GPUs and/or other accelerators (e.g. CUDA) Solid understanding of computer architecture fundamentals and how LLMs and Deep Learning models execute on that hardware (inference vs. training, matrix multiplication, KV-caching, etc.) Proficiency with profiling tools (NVIDIA Nsight, PyTorch Profiler … Pandas, NumPy) and scripting The following are also highly valued: Post-graduate degrees and research experience in relevant fields (please list your publications). Deep understanding of inference serving frameworks (e.g. vLLM) Background in statistical analysis Contributions to open source and/or research projects Benefits A collaborative ...

strong numerical and communication skills, turning data into insights and ideas into real‐world impact. You’ll have meaningful ownership from the start, while learning from talented colleagues across the business. It’s No Surprise We’re One Of The UK’s 100 Most Loved Workplaces. … Risk Lab The management of risk is an area where we see huge potential benefit from the application of large language models and associated deep learning techniques. You will apply your analytic skills to a wide range of challenges from across the business such as customer experience, financial ...

understanding of platform, DevOps and systems engineering.They also value genuine technical curiosity. If you keep up with new technology, experiment with AI/deep learning or have side projects outside your day job, they’ll want to hear about them.A STEM background is beneficial, but not essential.Nice ...

that actually forecast how a system will behave Hands-on GPU/accelerator code optimisation, CUDA or similar Genuine understanding of how LLMs and deep learning models run on real hardware, training versus inference, matrix multiplication, KV-caching, that level of detail Comfortable in profiling tools like Nsight ...

recent master's graduates with directly relevant coursework will also be considered A genuine, demonstrated grasp of computer architecture fundamentals and how LLMs and deep learning models actually run on hardware, training versus inference, matrix multiplication, KV-caching Real experience building performance models or forecasting tools, Python ...

work better. You'll report to the Head of AI Research and work closely with researchers covering genomics, computational biology, and large-scale deep learning. You'll also collaborate with the broader platform engineering and data teams across the company. About You PhD in computer science, physics, mathematics ...

growing team of Applied Scientists and AI/ML Engineers. This is a role for a pragmatic "Builder-Scientist" - a technical leader who possesses deep scientific rigor but is fundamentally driven by the iterative shipping of data products that customers fall in love with. You will lead the technical … Platform team to drive the overarching strategy for large language model operations (LLMOps), ensuring infrastructure supports efficient experimentation and robust deployment Apply deep scientific intuition to the design of AI systems, ensuring that models and data-intensive solutions are optimized for customer centricity and real-world performance ...

leading financial services firm is seeking an Applied AI ML Director specializing in NLP and LLM. The role involves developing machine learning solutions, collaborating with diverse teams, and driving innovative projects using cutting-edge techniques. Candidates should hold a PhD in a quantitative discipline and possess solid experience … deep learning frameworks and analytics. This is a unique opportunity to influence data-driven decision-making in a prominent organization, dedicated to fostering a highly collaborative work environment. #J-18808-Ljbffr ...

accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them … expanding presence in the Bay Area. The RolePhysicsX is building a platform that enables Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The platform handles massive volumes of complex simulation data and enables high fidelity multi physics simulation through AI inference. We are looking ...

J.P. MORGAN is seeking an NLP/LLM Scientist – Applied AI ML Lead to advance the Machine Learning Center of Excellence. You will tackle NLP, LLMs, and recommendation systems with deep learning methods. You will work with Business, Technology, Product, Legal, and Compliance to deploy robust ...

Researcher, you’ll work across the full research process, from framing the question and choosing the data to building, testing and deploying models. Machine Learning is central to the work, whether you’re extracting signals, forecasting prices or modelling relationships. Our data, compute and production infrastructure let you test … research end to end. That could include: Building models for pricing, forecasting and signal discovery, choosing the statistical, mathematical or Machine Learning methods that best fit the problem. Working across petabytes of market, order-flow and unstructured data to find signals that improve strategies as conditions change. Monitoring models ...

understand requirements and translate them into technical solutions Train and mentor junior engineers as we grow the UK team, fostering a culture of learning and improvement Stay updated with industry trends, emerging technologies, and best practices to enhance product development We’re looking for someone who has: Experience developing … autonomous vehicle solutions for aerospace and defence Experience with the end-to-end development cycle of deep learning models Expertise in subdomains such as modelling, input pipelines, evaluation, deployment, and model optimisation 5+ years of experience building production software using modern software practices Fluency in C++, or fluency ...

Position Summary FaceSwap is a new, exciting, and growing discipline within the visual effects industry, using Machine Learning (AI) to create digital faces and likenesses. We are currently looking for people with a keen eye for, and interest in, photo realism, as well as those comfortable with the technical … compositing is advantageous, artists with visual effects experience in any discipline are encouraged to apply. What You’ll Do Use a variety of deep learning based technologies to produce photorealistic images, including open source tools, and proprietary in house software Create templates to facilitate model evaluation Monitor ...

London Studio Req ID: 10160278 Job Description Position Summary: FaceSwap is a new, exciting, and growing discipline within the visual effects industry, using Machine Learning (AI) to create digital faces and likenesses. We are currently looking for people with a keen eye for, and interest in, photo realism … compositing is advantageous, artists with visual effects experience in any discipline are encouraged to apply. What You’ll Do Use a variety of deep learning based technologies to produce photorealistic images, including open source tools, and proprietary in house software Create templates to facilitate model evaluation Monitor ...

Markets is a leading algorithmic trading firm which uses state‐of‐the‐art machine learning technology to produce price forecasts for over 50,000 financial instruments across equities, fixed income, currencies, commodities, and crypto. It uses those forecasts to trade on exchanges and alternative trading venues, and to offer … have evolved considerably over the last 10 years, from econometric methods that gave our company its name, to trees, to neural networks, to modern deep learning architectures. XTX Markets has an unrivalled level of computational resources in the trading industry, with a growing research cluster currently containing over ...

Firm XTX Markets is a leading algorithmic trading firm which uses state-of-the-art machine learning technology to produce price forecasts for over 50,000 financial instruments across equities, fixed income, currencies, commodities, and crypto. It uses those forecasts to trade on exchanges and alternative trading venues … have evolved considerably over the last 10 years, from econometric methods that gave our company its name, to trees, to neural networks, to modern deep learning architectures. XTX Markets has an unrivalled level of computational resources in the trading industry, with a growing research cluster currently containing over ...

Wise’s FinCrime organisation, owning the full ML and AI foundation for financial crime detection. We're scaling into three dedicated pillars – Feature Platform, Learning Loop, and Risk Modelling. You'll sit in Risk Modelling, building the platform layer that makes scaling our detection capabilities possible. You’ll work … data scientist can use without writing deployment code Building model packaging and serving abstraction - a unified interface that handles multiple model types (classical ML, deep learning, emerging architectures) through a consistent API Implementing the model evaluation framework - standardised metrics, reproducible comparison, and automated validation gates Building model monitoring ...