451 to 475 of 1,243 Machine Learning Jobs

microservices, and backend systems. Solid understanding of software architecture, cloud infrastructure (AWS and/or Azure), and modern DevOps practices. Hands-on experience integrating ML models into production systems (LLMs via APIs, fine-tuning, RAG, embeddings, agents). Ability to move fast without compromising on code quality, testing, and operational ...

business stakeholders to accelerate value realisation across complex technology estates. Key Responsibilities AI Engineering & Delivery Design, build, and deploy production‐grade AI/ML solutions , including: LLM‐enabled applications (RAG, agents, copilots) Predictive models and intelligent automation AI services embedded into modernised platforms Own end‐to‐end AI lifecycle : discovery ...

major features, platforms, and technical initiatives Collaborate with technical leads and DevOps on system scalability, performance, and reliability Ensure data platforms are AI/ML-ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best ...

enter into a Data apprenticeship with formal study and training. You will gain/improve skills in SQL, Data visualisation, Advanced BI and Machine learning. Key Responsibilities Work with business management to design & build reporting dashboards. Interpret data, analyse results and provide ongoing reports with actionable output. Help ...

/JS Backend: R6, golem, plumber APIs Data: MariaDB (AWS RDS), S3, SQL optimization DevOps: GitHub Actions, Heroku, Digital Ocean, Docker, Git AI/ML: LLM APIs (OpenAI, Claude, etc.), ellmer package, Python LLM tooling, AI Agents Why SUSNEO? Innovation at Scale: Work on production applications that combine robust data ...

security best practices, monitoring, and incident response. Familiarity with DevSecOps and compliance frameworks (ISO 27001, SOC 2, GDPR). Exposure to big data processing, ML pipelines, or simulation workflows. Bonus: Existing interest in data science and simulation workflows in the manufacturing, energy or chemical process industries; Experience with high-performance ...

building real-world applications that incorporate large language models, agent based systems, and cloud based AI services. The role requires someone who enjoys experimenting, learning quickly, and applying new technologies in practical ways. Responsibilities: Design, develop, and deploy AI-enabled solutions using modern full stack technologies Integrate cloud-based … services (e.g. language models, machine learning, search, and cognitive APIs) into production systems Build and enhance features powered by large language models, including agent-style workflows and contextual integrations Work closely with clients to gather requirements and translate them into functional software solutions Contribute to technical discovery, prototyping ...

reimagining value creation capabilities. They are utilising cutting-edge AI to generate performance insights on each aspect of the investment lifecycle. Responsibilities: Build machine learning predictive models to anticipate/avoid asset downtime and reducing customer churn Evaluate … optimise all models, identifying areas for development Work end-to-end both building and deploying models Stay updated with the latest developments in ML/AI, and related fields to keep the company at the forefront of technological advancements Stay updated on emerging technologies, trends, to recommend and implement innovative ...

Requirements Current Head of AI, Head of Data Science, or Senior AI Lead ready to step up. Proven experience building and scaling AI/ML teams (0–10/0–15) . Insurance experience Strong technical credibility in ML, AI, and enterprise platforms. Hands-on experience with Azure, Databricks … ML tools (TensorFlow, PyTorch, Scikit-learn). Knowledge of Responsible AI, ethical frameworks, and compliance standards . Experience in insurance or regulated financial services preferred. Comfortable presenting to and influencing executives . Collaborative, adaptable, and able to navigate complex stakeholder environments . To apply: Please reach out via LinkedIn ...

Close collaboration from cloud strategy through to delivery Access to leading experts across cloud, AI, data, and engineering A culture built on innovation, continuous learning, and shared success The opportunity to work with some of the biggest and most complex organisations in the UK This is an environment … secure, scalable cloud architectures Skilled in cost optimisation and cloud best practices Data & AI Strong understanding of data platforms, analytics solutions, and AI/ML-driven architectures Application Architecture Experience with serverless, microservices, and containerised workloads Familiarity with CI/CD pipelines and DevOps practices Security Architecture Deep knowledge ...

bridge between engineering, product, and commercial. What I’m Looking For 8+ years of engineering leadership within B2B SaaS, ideally in AI/ML or data-focused environments. Experience growing teams through start-up to scale-up (Series A/B); time in both early-stage and mature environments … continuous delivery, and high-performing lean teams. People-first leadership style, with a proven ability to build and nurture high-performing teams. Exposure to machine learning, NLP, or financial data products is highly advantageous. Comfortable working in fast-moving, ambiguous environments where both execution and strategic vision matter. ...

/m/d) who is passionate about building reliable data products and pipelines, enabling data driven development, and supporting the deployment of scalable machine learning solutions in an AWS environment. In this project-based role, you can work from anywhere in Austria. The position is available immediately … data interfaces and requirements Design and implement scalable data pipelines using the AWS technology stack Support automation of data science workflows and ensure repeatable ML deployments Profil 3+ years of experience working with large-scale data and building reliable data pipelines Strong programming skills in Python and SQL, plus hands ...

enabled products and solutions using modern architectures including: LLM-based applications RAG pipelines AI orchestration layers agent-based systems Work closely with data scientists, ML engineers, and data engineers to move ideas from concept to implementation. Evangelism & Thought Leadership Act as an internal and external advocate for practical AI adoption … roles Strong understanding of generative AI ecosystems and large language models Exposure to modern AI architectures and system design Experience shaping or delivering AI, machine learning, or advanced analytics initiatives Ability to move from strategic conversation to practical implementation Strong communication and stakeholder engagement skills Technical Awareness Candidates ...

getting interviews but not offers, you're closer than you think-yet that final gap can feel brutal. Many candidates spend months learning frameworks and finishing courses, only to freeze during technical screens, system questions, or behavioral rounds. The result is painful: "almost hired" over and over again, while … Learning Engineers. The focus areas include Java/Full Stack/DevOps and Data tracks like Data Engineering, Data Analytics/BI, ML/AI, because those are the roles employers continue to hire for. If your pattern is "I reach interviews but don't clear them ...

scalable solutions that meet customer-specific requirements Work directly with clients to gather requirements, provide technical guidance, and serve as the post-go-live ML point of contact Develop custom APIs and backend services to enable seamless integration with customer environments Troubleshoot and resolve complex technical issues, acting … between customers and the engineering team Deliver small, targeted features to unblock high-priority edge cases and resolve customer tickets Partner closely with the ML team on inference/data pipeline issues, adding validation and guardrails where needed Collaborate with Product, Engineering, Customer Success, and Sales to refine features, improve ...

solve business problems. Candidates who display exceptional competencies in collaborative, multi-disciplinary working and strong leadership characteristics will be considered alongside technical competencies in machine learning, artificial intelligence and natural language processing. Main duties of the job The Senior Data Scientist role will support the Data Science Manager … understands related legislation Experience of direct line management of staff Knowledge Essential Broad understanding of data engineering and processing environments including Azure Datalake, ML Ops, Data Factory and Databricks Broad understanding of current NHS, national, regional, and local context Knowledge of statistical techniques (regression, classification, decision trees,supervised/unsupervised ...

between cost, latency, and production-scale performance. What you'll bring Proven extensive lead-level engineering experience delivering sports insights or sports data–driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data … other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi-modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands ...

führenden Premium-Hersteller von Automobilen sowie Motorrädern und darüber hinaus Anbieter von Premium-Finanz- und Mobilitätsdienstleistungen. Am Standort München suchen wir Sie als Senior ML Ops Engineer - Architecture & Strategy (f/m/x) INNOVATION IS IMAGINING WHAT NO ONE ELSE CAN. At the BMW Group, everything begins with passion. … expertise, highly professional processes, and enjoyment of work come together that we can shape the future collectively. We own the platform blueprint for our ML infrastructure: designing systems that integrate with a data mesh of domain-owned data products, leverage Qualcomm Cloud AI 100 and NVIDIA GPU clusters for training ...

Software Engineer (Python/Django) About the role: We are working with an early-stage, AI-driven technology company building advanced platforms that leverage machine learning, NLP and large language models to solve complex research and data problems. The team is focused on developing scalable, intelligent systems , increasingly ...

Science, Statistics, Mathematics, or a related field (Master’s or Ph.D. preferred). Proficiency in programming languages, particularly Python, R, and SQL. Experience with machine learning techniques and frameworks (e.g., TensorFlow, Scikit-learn). Strong analytical skills with a knack for problem-solving and critical thinking. Excellent communication ...

record of working cross-functionally and influencing stakeholders Nice to Have Combination of vendor + banking/financial services experience Experience applying AI/machine learning within fraud or risk environments Exposure to fast-paced, high-growth or product-focused businesses What's on Offer Salary from ...

opportunity to work at the heart of a highly data-driven trading environment, building the platforms and pipelines that power advanced analytics, machine learning and systematic trading strategies. The firm operates across global energy and commodities markets and is known for combining quantitative research, advanced analytics and modern ...

currently studying for a degree in relevant subject areas: Computer Science Information Systems/Information Technology Software Engineering Data Science & Analytics Artificial Intelligence & Machine Learning Cloud Computing Business Information Management We welcome applications from students who: Have strong communication and organisational skills Are proactive, eager to learn ...

generative AI solutions within the Microsoft ecosystem . This position is well-suited for candidates with a background in software engineering, data science, or machine learning who excel at developing production-grade AI applications utilizing Microsoft platforms such as M365, Copilot Studio, and Azure AI Foundry, and have ...

platforms such as Microsoft, AWS, Google or OpenAI technologies Practical exposure to Generative AI and large language model frameworks Skills in data analysis and machine learning tooling (Python, SQL, R or similar) Confidence engaging with senior stakeholders and translating technical concepts into clear business value Experience contributing ...