1 to 25 of 108 Distributed Computing Jobs in London

a related field, with 10+ years of experience in software architecture (including 5+ years in AI/ML systems). Proven track record of designing and implementing large-scale, distributed AI systems. Deep understanding of AI and machine learning (natural language processing, computer vision, predictive modelling). Extensive experience with cloud platforms (AWS, Google Cloud, Azure) and their AI … databases and analysis tools. Knowledge of AI model serving frameworks like TensorFlow Serving or ONNX Runtime. Experience with AI ethics and bias mitigation techniques. Familiarity with GPU acceleration and distributed computing for AI workloads. Why Join warpSpeed: Career Growth and Impact: Technical Leadership and Innovation: Lead the architectural vision for a revolutionary Application AI platform. Opportunity to solve … complex technical challenges at the intersection of AI, cloud computing, and productivity tools. Influence the direction of AI applications in daily software tools. Career Growth and Impact: Play a key role in a rapidly growing startup that's redefining productivity in the AI era. Opportunity to shape the future of work and personal productivity for millions of users. Clear More ❯

consistent data from external APIs and ensuring seamless incorporation into existing systems. Big Data Management and Storage : Utilize PySpark for scalable processing of large datasets, implementing best practices for distributed computing. Optimize data storage and querying within a data lake environment to enhance accessibility and performance. ML R&D : Collaborate on model prototyping and development, identifying the most relevant … 3+ years of experience in applying machine learning in a commercial setting, with a track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially More ❯

consistent data from external APIs and ensuring seamless incorporation into existing systems. Big Data Management and Storage : Utilize PySpark for scalable processing of large datasets, implementing best practices for distributed computing. Optimize data storage and querying within a data lake environment to enhance accessibility and performance. ML R&D : Collaborate on model prototyping and development, identifying the most relevant … 3+ years of experience in applying machine learning in a commercial setting, with a track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially More ❯

consistent data from external APIs and ensuring seamless incorporation into existing systems. Big Data Management and Storage : Utilize PySpark for scalable processing of large datasets, implementing best practices for distributed computing. Optimize data storage and querying within a data lake environment to enhance accessibility and performance. ML R&D : Collaborate on model prototyping and development, identifying the most relevant … 3+ years of experience in applying machine learning in a commercial setting, with a track record of delivering impactful results. Extensive programming skills in Python, with a specialization in distributed computing libraries such as PySpark. Extensive experience with PyTorch (preferred) and/or TensorFlow. Hands-on experience with deploying machine learning models in production using cloud platforms, especially More ❯

for data augmentation, denoising, and domain adaptation to enhance model performance. 3. Model Training and Optimization: -Design and implement efficient training pipelines for large-scale generative AI models. -Leverage distributed computing resources, such as GPUs and cloud platforms, for efficient model training. -Optimize model architectures, hyperparameters, and training strategies to achieve superior performance and generalization. 4. Model Evaluation … experiences, don't let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. … BERT, or T5. - Familiarity with reinforcement learning techniques and their applications in generative AI. - Understanding of ethical AI principles, bias mitigation techniques, and responsible AI practices. - Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Apache Spark, Dask). - Strong problem-solving, analytical, and critical thinking skills. - Strong communication, collaboration, and leadership More ❯

Python, Java, or Scala) Extensive experience with cloud platforms (AWS, GCP, or Azure) Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks (Spark, Kinesis etc) Software development best practices including CI/CD, TDD and version control. Strong understanding of data modelling and system architecture Excellent problem-solving More ❯

Python, Java, or Scala) Extensive experience with cloud platforms (AWS, GCP, or Azure) Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks (Spark, Kinesis etc) Software development best practices including CI/CD, TDD and version control. Strong understanding of data modelling and system architecture Excellent problem-solving More ❯

Spark, PySpark, TensorFlow . Strong knowledge of LLM algorithms and training techniques . Experience deploying models in production environments. Nice to Have: Experience in GenAI/LLMs Familiarity with distributed computing tools (Hadoop, Hive, Spark). Background in banking, risk management, or capital markets . Why Join? This is a unique opportunity to work at the forefront of More ❯

application platform development, web and mobile development, cloud, integration, security, etc. " Application dev experience with at least one of the cloud providers - Amazon AWS or MS Azure " Understanding of distributed computing paradigm and exposure to building highly scalable systems. " Experience with platform modernization and cloud migration projects " Expertise in Agile development methodologies like TDD, BDD, Performance/Load More ❯

Quant and Front Office technology teams to integrate pricing models and workflow enhancements within the ACE application. There will be exposure to a wide range of technological frameworks, including distributed computing architecture. The role will involve tasks such as: Developing and maintaining the Counterparty Credit Risk applications, leveraging in-house Python and C++ model libraries. Supporting and improving More ❯

re comfortable developing or learning to develop custom metrics, identify biases, and quantify data quality. Strong Python skills for Data & Machine Learning, familiarity with PyTorch and TensorFlow. Experience with distributed computing and big data - scaling ML pipelines for large datasets. Familiarity with cloud-based deployment (such AWS, GCP, Azure, or Modal). Experience in fast moving AI, ML More ❯

forecasting and planning for the Physical Consumer business. We are building the next generation Business Intelligence solutions using big data technologies such as Apache Spark, Hive/Hadoop, and distributed query engines. As a Data Engineer in Amazon, you will be working in a large, extremely complex and dynamic data environment. You should be passionate about working with big … engineering leaders, and business leaders to build data architectures and platforms to support business - Design, develop, and operate high-scalable, high-performance, low-cost, and accurate data pipelines in distributed data processing platforms - Recognize and adopt best practices in data processing, reporting, and analysis: data integrity, test design, analysis, validation, and documentation - Keep up to date with big data … and load (ETL) data from a wide variety of data sources - Own the functional and nonfunctional scaling of software systems in your ownership area. - Implement big data solutions for distributed computing. Key job responsibilities As a DE on our team, you will be responsible for leading the data modelling, database design, and launch of some of the core data More ❯

Optimise market data pipelines and trade execution engines to improve performance and reduce latency. Ensure system reliability, scalability, and low-latency performance in a fast-paced trading environment. Utilise distributed computing and high-performance computing techniques to enhance algorithmic execution. Integrate with exchange APIs (REST/WebSocket/FIX) for real-time data processing and trading execution. … Required Qualifications: Strong understanding of quant trading logic, market structure, and execution strategies. Proficiency in C++ and Python, with experience in high-performance computing, multi-threading, and distributed systems. Experience with algorithmic trading systems in crypto, equities, FX, or derivatives at least 5 years. Knowledge of financial markets, risk management, and portfolio optimisation. Solid understanding of data structures … s, Master’s, or PhD in Computer Science, Mathematics, Engineering, or related fields. Preferred Qualifications: Experience with low-latency trading systems and high-frequency trading (HFT). Background in distributed computing, machine learning, or AI-driven trading models. Familiarity with cloud computing, Kubernetes, or containerised environments. Strong debugging, profiling, and performance optimisation skills. What We Offer: Competitive More ❯

Optimise market data pipelines and trade execution engines to improve performance and reduce latency. Ensure system reliability, scalability, and low-latency performance in a fast-paced trading environment. Utilise distributed computing and high-performance computing techniques to enhance algorithmic execution. Integrate with exchange APIs (REST/WebSocket/FIX) for real-time data processing and trading execution. … Required Qualifications: Strong understanding of quant trading logic, market structure, and execution strategies. Proficiency in C++ and Python, with experience in high-performance computing, multi-threading, and distributed systems. Experience with algorithmic trading systems in crypto, equities, FX, or derivatives at least 5 years. Knowledge of financial markets, risk management, and portfolio optimisation. Solid understanding of data structures … s, Master’s, or PhD in Computer Science, Mathematics, Engineering, or related fields. Preferred Qualifications: Experience with low-latency trading systems and high-frequency trading (HFT). Background in distributed computing, machine learning, or AI-driven trading models. Familiarity with cloud computing, Kubernetes, or containerised environments. Strong debugging, profiling, and performance optimisation skills. What We Offer: Competitive More ❯

technologies, including application platform development, web and mobile development, cloud, integration, security, etc. Application development experience with at least one cloud provider - Amazon AWS or MS Azure Understanding of distributed computing paradigms and exposure to building highly scalable systems. Experience with platform modernization and cloud migration projects. Expertise in Agile development methodologies like TDD, BDD, performance/load More ❯

application platform development, web and mobile development, cloud, integration, security, etc. Application dev experience with at least one of the cloud providers - Amazon AWS or MS Azure Understanding of distributed computing paradigm and exposure to building highly scalable systems. Experience with platform modernization and cloud migration projects Expertise in Agile development methodologies like TDD, BDD, Performance/Load More ❯

application platform development, web and mobile development, cloud, integration, security, etc. Application dev experience with at least one of the cloud providers - Amazon AWS or MS Azure Understanding of distributed computing paradigm and exposure to building highly scalable systems. Experience with platform modernization and cloud migration projects Expertise in Agile development methodologies like TDD, BDD, Performance/Load More ❯

application platform development, web and mobile development, cloud, integration, security, etc. Application development experience with at least one of the cloud providers - Amazon AWS or MS Azure Understanding of distributed computing paradigm and exposure to building highly scalable systems. Experience with platform modernization and cloud migration projects Expertise in Agile development methodologies like TDD, BDD, Performance/Load More ❯

emphasis on deploying ML models to production quickly. - Knowledge of deep learning models and frameworks, and interest in exploring cutting-edge ML techniques. - Experience working with large datasets and distributed computing environments. - Excellent organisational, analytical and influencing skills, with proven ability to take initiative and build strong, productive relationships. - Experience working with cross-functional teams within a software More ❯

Machine Learning Engineer, Amazon General Intelligence (AGI) Job ID: Services LLC - A57 Our Machine Learning training infrastructure (ML Infra) team is responsible for designing, implementing, and optimizing large-scale computing infrastructure that powers our cutting-edge AI and machine learning initiatives. We leverage advanced hardware, innovative software architectures, and distributed computing techniques to enable breakthrough research and … scout top talent and recruit them to the company. - Actively mentor senior and Principal engineers, scale yourself by developing and institutionalizing best practices in AI/ML infrastructure and distributed computing across the organization. A day in the life 8+ years of professional software development experience in distributed systems with emphasis on ML infrastructure - 8+ years of … current programming experience building ML infrastructure using languages such as Python, C++ or Rust - Hands-on experience with parallel computing platforms such as CUDA, OpenMP, etc - Deep understanding of AI frameworks such as PyTorch, TensorFlow, and JAX, and their demands on underlying compute infrastructure, memory bandwidth, network interconnect, and storage as scale goes up - Knowledge of emerging AI hardware More ❯

AI revolution! About DeepPCB: DeepPCB is InstaDeep's AI-powered Place & Route PCB (Printed Circuit Board) design tool. We use a combination of deep reinforcement learning and high-performance computing to automate and scale PCB place-and-route workflows, accelerating hardware innovation globally. We are looking for a Machine Learning Engineer to join the DeepPCB team and help push … engineers to bring ideas to life. Responsibilities: Develop scalable and efficient machine learning algorithms to tackle PCB place-and-route challenges. Adapt and optimize ML models for large-scale distributed computing environments (e.g., GPUs, multi-node clusters). Build, test, and deploy robust production-level ML systems integrated into the DeepPCB platform. Collaborate with research scientists, software engineers … thrive in a fast-paced, collaborative, and dynamic environment. Nice to haves: Prior experience with PCB design, EDA tools, or related optimization problems. Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask). Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle). Expertise in related fields such as Computer Vision More ❯

and monitoring in production systems Experience with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Experience with natural language processing (NLP) e.g., Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

SQL, PERL/scripting . Skilled Data Engineer for Cloud Data Lake activities. The candidate should have industry experience (preferably in Financial Services) in navigating enterprise Cloud applications using distributed computing frameworks as Apache Spark, Hadoop, Hive. Working knowledgeoptimizing database performance, scalability, ensuring data security and compliance. Education & Preferred Qualifications Bachelor's/Master's Degree in a More ❯

and monitoring in production systems Experience with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer More ❯

and monitoring in production systems Experience with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer More ❯