Data science állások Budapesten (it programozás, fejlesztés)

• Design and build agentic systems that plan, call tools and automate real business workflows
• Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration

• Lead annual and periodic User Developed Application (UDA) assessments and certifications, ensuring compliance with bp controls and regulatory requirements
• Partner with participants, application owners and technical teams to identify, assess and remediate control gaps, reducing risk

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients

• Design, implement, and optimize compiler passes and transformations using LLVM/Clang or GCC
• Build and maintain robust toolchains
• Support new and complex architectures in compiler backends
• Work on architecture-agnostic and IR-level optimizations
• Work on silicon specific optimizations

Working on the design, development, and production of advanced digital solutions, ensuring seamless integration with existing infrastructure and adherence to enterprise architecture standards and robust delivery lifecycle processes. This includes leveraging expertise in various digital technologies...

Act as the primary functional LMS expert and support lead for learning systems within the HR organization, with a strong focus on the current LMS (e.g. Cimoio) and the transition to SAP SuccessFactors Learning,...

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Trade a wide range of financial instruments
• Develop, maintain, and improve trading strategies and algorithms
• Run trading desks and support day-to-day trading operations
• Manage execution and risk across complex trading portfolios
• Analyze market data and identify opportunities for strategy improvement

• nagy mennyiségű adat feldolgozását támogató adatfolyamatok tervezése és fejlesztése,
• adatbetöltési, adattranszformációs és adatminőség-ellenőrzési folyamatok kialakítása,
• adatforrások integrálása, strukturált és félig strukturált adatok kezelése,

• Owning a revenue target across data, advanced analytics, and predictive AI
• Leading executive-level client conversations, joining deals early to diagnose the business problem, structure a solution, and build the ROI case that gets the client to sign

• Designing and building AWS infrastructure and landing zones
• Defining AWS infrastructure using Terraform or OpenTofu with Terragrunt, or AWS CloudFormation
• Building CI/CD pipelines
• Leading migrations of customer workloads from on-premises, GCP, Azure, or Heroku to AWS

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM to deploy models efficiently
• Implementing and optimizing ML models using techniques such as quantization, kernel fusion, and efficient batching

• Research, configure, and test AI tools including Claude, Gemini, Zapier, and n8n to improve the GTM stack
• Build proof-of-concepts for AI-driven lead research, automated email drafting, meeting summarization, and information hand-offs

• üzleti és technikai adatforrásokból származó adatok összegyűjtése, tisztítása és strukturálása
• adatmodellek kialakítása (DWH szemlélettel), adatstruktúrák felépítése
• komplex SQL lekérdezések és adattranszformációk készítése, teljesítményoptimalizálása

• Development, adaptation, and deployment of end-to-end tracking solutions for sports officiating and analytics
• Implementation and optimization of ML models using Python, C++, PyTorch, NumPy, Pandas, and OpenCV
• Design and building of ETL pipelines and data manipulation workflows

Process Design & Optimization: Design and continuously improve end-to-end Requisition-to-Receipt (R2R) processes, implementing best practices, automation opportunities, and intelligent workflows including guided buying, supplier punchouts, and catalog-driven purchasing for Direct and Indirect...

• Search, collect, consolidate, and validate financial and non-financial data across departments and systems
• Design, build, maintain, and automate dashboards and underlying data pipelines to provide timely, accurate insights to stakeholders

• Architecting complex AWS infrastructures and zero-day compliant landing zones
• Understanding customers’ business problems and providing technology consulting to identify the best-fit solution
• Owning the end-to-end solution as a key decision-maker and driving the delivery team

• Delivery on complex projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent