201 to 225 of 3,462 Permanent Algorithms Jobs

AWS EMEA SARL (UK Branch) - F93 Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge Generative AI algorithms to solve real world problems with significant impact? The AWS Industries Team at AWS helps AWS customers implement Generative AI solutions and realize transformational business opportunities for AWS customers in … You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. In this Data Scientist role you will be capable of using GenAI and other techniques to design, evangelize, and … edge solutions for never-before-solved problems. Key job responsibilities Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms and build ML systems to address real-world challenges. Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing More ❯

all stages of the data lifecycle Develop and maintain ETL processes for data ingestion and processing Algorithm Development, Model Training and Optimisation Design, develop, and implement advanced machine learning algorithms for fraud prevention and user personalization Train and fine-tune machine learning models using relevant datasets to achieve optimal performance Implement strategies for continuous model improvement and optimization Data Mining … to extract meaningful insights and features for model training Code Review and Documentation Conduct code reviews to ensure high-quality, scalable, and maintainable code Create comprehensive documentation for developed algorithms and models Collaboration Collaborate with our cross-functional team; including the founders, sales, data scientists, engineers, and product to understand business requirements and implement effective solutions Research and Innovation Stay … Data Science, or a related field. 7+ years of professional experience in a relevant area like fraud prevention or credit scoring Machine Learning Expertise: Strong understanding of machine learning algorithms and their practical applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and More ❯

data science . You’ll join a cross-functional squad (engineering, ops, analytics, and DS) working on complex challenges in first, middle, and last-mile delivery. From designing smarter algorithms to unlocking efficiency across the network, your work will directly impact cost, sustainability, and speed at scale. What You’ll Be Doing Designing, testing, and deploying optimisation algorithms to improve More ❯

an exceptional Senior AI Engineer with a strong machine learning and AI background to join our team. In addition to exceptional programming skills and knowledge of data structures and algorithms, the ideal candidate should also be proficient in the mathematical underpinnings of deep learning and deeply understand modern AI techniques. As a Senior AI Engineer, you will be responsible for … preferred. Minimum six years of experience in AI engineering, machine learning, or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication More ❯

Engineer and you will have the opportunity to: Collaborate with colleagues on production systems and write, test, and maintain production quality code Design, train, experiment, and evaluate ML models, algorithms and solutions Demonstrate technical leadership by owning cross-team projects Stay current with the latest research in AI and incorporate new findings into our models and methodologies Represent Bloomberg at … in CS, ML, Math, Statistics, Engineering, or related fields and previous relevant work experience Proficiency in software engineering An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders. A track record of authoring More ❯

the opportunity to drive the architectural roadmap, whilst looking to optimise away manual inefficiencies. Example Projects The team has helped develop a number of modular building blocks Low-latency Algorithms for Automated Trading and Systematic Market Making Real-time streaming pipelines and signals Pricing libraries and tooling Venue connectivity for automated fund movement and management. By the end of … test, and refine alpha signals and systematic trading strategies across asset classes. Design and rigorously backtest trading models, ensuring statistical robustness and real-world applicability. Develop and optimize execution algorithms (VWAP, TWAP, Participation, SOR) to enhance trading performance and minimize market impact. Monitor and maintain real-time trading systems, proactively addressing issues in execution, risk, and P&L. Perform post … strong skills in Java and/or Python. Proficient in Python’s data science ecosystem (Pandas, NumPy, Scikit-learn) with solid debugging and analytical capabilities. Demonstrated experience implementing trading algorithms and working on large-scale distributed systems. Familiarity with transactional systems using modern databases like Aurora or DynamoDB. Exposure to front-office trading environments, ideally with FX or crypto markets. More ❯

role is essential for driving insights, automating processes, and delivering impactful business outcomes. Key Responsibilities ML and AI Model Development Design, build, and deploy machine learning models using advanced algorithms, including AutoML techniques. Develop and fine-tune models for regression, classification, clustering, and deep learning. Explore and implement state-of-the-art AI approaches such as transformer models, generative AI … related field. Equivalent experience will be considered. Experience Minimum of 5 years in a data science or machine learning-focused role. Technical Skills Expertise in designing and deploying ML algorithms, AutoML tools, and AI applications. Proficiency with programming languages such as Python and R, and ML libraries (TensorFlow, PyTorch, scikit-learn). Hands-on experience with cloud platforms (Azure ML More ❯

systems to support RLDatix’s mission of enabling safer, more efficient healthcare worldwide. How You’ll Spend Your Time Designing and developing machine learning models, large language models, and algorithms to deliver meaningful insights from large datasets. Establishing and maintaining ETL workflows and data pipelines in order to ensure data consistency, quality, and usability across the platform. Optimizing machine learning … as Python and SQL. Experience with data processing and analysis tools and technologies like TensorFlow, Keras, Scikit-learn. Strong understanding of large language models (LLMs) and machine learning (ML) algorithms and techniques. Familiarity with data visualization tools such as Power BI. Solid understanding of statistical analysis and hypothesis testing. Ability to work with structured and unstructured data sources. Knowledge of More ❯

As an AI/ML Python Engineer at JPMorgan Chase within the Client Onboarding and KYC Engineering team, your responsibilities will include probing intricate business problems and employing sophisticated algorithms to design, evaluate, and implement AI/ML applications or models to resolve these issues. You will be required to leverage the company's extensive data assets from both internal … sentiment analysis, basic transformers for text-heavy datasets. Experience with LLM & Prompt Engineering, including tools like LangChain, LangGraph, and Retrieval-Augmented Generation (RAG). Experience in anomaly detection techniques, algorithms, and applications. Excellent problem-solving, communication (verbal and written), and teamwork skills. Preferred qualifications, capabilities, and skills Experience with big data frameworks, with a preference for Databricks. Experience with databases More ❯

in Computer Science, Data Science, or a related field (or equivalent practical experience). - 2-3 years of experience in machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). - Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. - Strong Python and Java programming skills and … familiarity with NLP algorithms and libraries. - Solid understanding of basic statistics and how to apply it to real-world machine learning tasks. - Familiarity with cloud platforms (AWS) and Kubernetes for deploying and scaling models. - A passion for solving problems with data and machine learning, always looking for ways to get things done quickly and effectively. - A proactive, results-driven mindset More ❯

build processes PREFERRED QUALIFICATIONS PREFERRED QUALIFICATIONS - Experience in systems development with a focus on large-scale data systems, knowledge graphs, or graph-based technologies - Strong knowledge of data structures, algorithms, big "O" analysis and designing for performance, scalability and availability - Strong understanding of graph data structures, algorithms, and graph database technologies - Experience as a mentor, tech lead, or leading an More ❯

us in shaping the future of gaming. Are you ready to LEVEL-UP THE GAME? The role We are building the sportsbook of tomorrow at Kindred Group. Machine learning algorithms and AI are at the heart of how we will deliver an unrivalled customer experience and unlock operational efficiencies through automation. Our Data Science (DS) and Machine Learning Engineering (MLE … in sports personalisation & recommendations. Excellent interpersonal skills, able to explain complex concepts to stakeholders. Ability to coach, support and mentor more junior team members. Advanced knowledge of machine learning algorithms and general statistical methodologies and theory. Advanced knowledge of AB testing and design of experiment. Advanced Python and SQL skills, experience using Spark for processing large datasets. Understanding of software More ❯

to help them develop technical excellence. Essential Qualifications and skills Will have 4-5 years' experience as a data scientist with proven ability to conceptualize, formulate, prototype and implement algorithms to solve complex business problems. Can coordinate and manage competing priorities across a portfolio of projects Compile, integrate, and analyse data from multiple sources to answer business questions Experience communicating … to both technical and non-technical audiences to facilitate feasibility assessment, prioritisation and adoption. Have scientific mindset and understanding of statistical modelling and the mathematical foundations of Machine Learning algorithms Proficient in Python Have a deep knowledge of a sufficiently broad area of technical specialism (e.g. Time Series, Combinatorial Optimisation, Reinforcement Learning, Bayesian Statistics, NLP etc.) Good knowledge in mining More ❯

coursework (typically 5 or more courses) in advanced mathematics (typically 300 level or higher; such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper-level math courses designated as … elementary or basic do not count. Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g. C , data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time More ❯

techniques along with performing statistical analyses leading to the understanding of the structure of data sets. Proven and demonstrable experience with at least three of the following machine learning algorithms: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. Experience working with Java and Python, and strong understanding of data … structures, algorithms, and software design patterns. Experience with AI and Gen AI frameworks (e.g., TensorFlow or PyTorch). Experience with at least one cloud-based platform (e.g., AWS SageMaker or Azure Machine Learning). Adept at translating business problems into solution statements. Strong communication skills and bilingualism/multilingualism are highly desirable. Open for travel (50% — national and international travel More ❯

data engineering team. Uncover novel biological insights into disease, spanning complex and rare diseases, and develop methods to validate new drug targets. Evaluate the scientific and technical integrity of algorithms and tools within the analysis pipeline. Work closely with discovery and development teams to integrate genomic and histology imaging analysis. Communicate findings effectively to both technical and non-technical audiences. … Key Qualifications: PhD (or equivalent experience) in Machine Learning, Computational Biology, Bioinformatics, or a related quantitative field. Strong programming skills with a solid understanding of algorithms and data structures. Proficiency in Python with hands-on experience using open-source ML frameworks such as scikit-learn, PyTorch, TensorFlow, or Keras. Extensive experience with Machine Learning and Deep Learning models (e.g., tree More ❯

selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline’s extensive datasets and state of the art algorithms Create the tools, frameworks and libraries that enables the acceleration of our ML products delivery and improve our workflows Take an active part in our AI and ML community and … Nice to have Hands-on building large-scale reinforcement learning solutions for content recommendation Experience with transport industry Experience with cloud infrastructure Experience with graph technology and/or algorithms Have experience with NLP, designing, fine-tunning and developing GenAI models and building agent AI systems Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM More ❯

is a plus) 2+ years of professional experience as in C++ Development Modern C++ programming experience in C+/20 or above Knowledge of design patterns, data structures and algorithms Ability to write efficient, high performing code. Strong analytical and problem-solving skills Solid communication skills Able to work as part of a team in a fast-paced environment Detail More ❯

assessment. We also build LLM-powered systems for automating and accelerating cybersecurity risk assessment workflows. About the Role: As an ML Engineer, you will design and optimize machine learning algorithms, build scalable data pipelines, and deploy reliable models into production environments. You'll collaborate with cross-functional teams to integrate ML solutions into products, conduct research to stay ahead of … with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. Proficiency in data manipulation and analysis using tools such as Polars, Pandas, NumPy, or SQL. Solid understanding of algorithms, statistics, and data structures. Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Knowledge of CI/CD pipelines and version control systems (e.g. Git). Familiarity More ❯

to Portfolio and Risk Managers Required skills/experience: Strong analytical and mathematical skills, with interest and/or exposure to quantitative finance Good understanding of various design patterns, algorithms, and data structures Substantial experience with modern Java Experience with REST APIs and cloud services Relational SQL database development experience Unix/Linux command-line experience Ability to work independently More ❯

assessment. We also build LLM-powered systems for automating and accelerating cybersecurity risk assessment workflows. About the Role: As an ML Engineer, you will design and optimize machine learning algorithms, build scalable data pipelines, and deploy reliable models into production environments. You'll collaborate with cross-functional teams to integrate ML solutions into products, conduct research to stay ahead of … with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. Proficiency in data manipulation and analysis using tools such as Polars, Pandas, NumPy, or SQL. Solid understanding of algorithms, statistics, and data structures. Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Knowledge of CI/CD pipelines and version control systems (e.g. Git). Familiarity More ❯

qualification is a plus) 2+ years of professional experience in C++ Development Modern C++ programming experience in C++17/20 or above Knowledge of design patterns, data structures, and algorithms Ability to write efficient, high performing code Strong analytical and problem-solving skills Solid communication skills Able to work as part of a team in a fast-paced environment Detail More ❯

Our massively scaled out distributed systems process hundreds of millions of updates on the billions of products across physical, digital, and services offerings. To achieve this, we develop the algorithms and build the systems and tools to ensure the safety of the selection and maximize their impact on the Amazon top-line, all the while continuously growing the overall selection. … Our massively scaled out distributed systems process hundreds of millions of updates on the billions of products across physical, digital, and services offerings. To achieve this, we develop the algorithms and build the systems and tools to ensure the safety of the selection and maximize their impact on the Amazon top-line, all the while continuously growing the overall selection. More ❯

JavaScript is preferred. Experience with AI/ML frameworks and libraries is a significant asset. Production experience with Cloud and ML technologies Experience working in the below areas and algorithms will be ideal but not mandatory: Generative AI Modeling: Customizing LLM's, build and deploy LLM's at scale for large scale data generation Algorithms: Transformer models, Attention mechanism, Prompt More ❯

Transformers, graph neural networks) in real-world applications. Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.). Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git). Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent). Solid understanding of data-engineering … Collaborative Attitude: You value cross-functional teamwork and can pivot between researcher mode and software engineer mode depending on the task at hand. Growth-Oriented: You continually learn new algorithms, architectures, and engineering best practices; you encourage team members to do the same. What We Offer Equity Package: Meaningful ownership stake, commensurate with an early leadership role. Competitive Compensation: Salary More ❯