Python állások, munkák it tanácsadó, elemző, auditor kategóriában

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

You will analyse and evaluate technological developments and market trends in the areas of blockchain, DLT, smart contracts, tokenisation, CBDC and artificial intelligence....

Tailor the SAP-RPT model family to the unique complexities of real-world relational enterprise data, enabling models to navigate and reason over intricate schemas and logic...

• Line management, coaching, and career development for a team of Full-Stack Engineers
• Performance management and professional growth fostering
• Fostering a culture of technical excellence

• Developing and evaluating AI systems based on Large Language Models (LLMs), Vision-Language Models (VLMs), and multimodal foundation models
• Designing agentic workflows that automate complex image analysis tasks

Design and maintain scalable dashboards that empower the Commercial Solutions team to make faster, data-driven decisions around pricing and commercial product performance...

Analysis of the data ecosystem: assessment of data systems, interfaces and data quality; evaluation of security / privacy and interoperability (data-level to user-level)...

• Keep data moving: Build, run, and refine data pipelines and workflows (Python, Airflow/Cloud Composer) so they're reliable, fast, and easy to change
• Shape our data models: Use BigQueryand Cloud Spanner to design wellstructured, highperformance datasets for analytics and machinelearning use cases

• You understand RABOT's departments, their core processes and our AI tooling (Claude, Claude Code, our data stack) well enough to run a process-discovery session on your own.
• You've shipped your first automation into production — something a team feels immediately.

• Implementing and evaluating state-of-the-art quantum algorithms (e.g., QAOA, VQE, quantum annealing or others) for an optimization problem in the scope of optical systems
• Implement prototypes and demonstrators to evaluate quantum-enhanced optimization concepts for ZEISS applications

Ownership of Data Assets & strategy: Own pre-training, evaluation, and meta-data including proprietary, open-source, and synthetic datasets. Develop and execute vision....

Own SEO data pipelines end-to-end. Design, build, and maintain automated pipelines that power all SEO analytics, from ingestion through transformation to dashboarding....

Lead, Plan, and Deliver: You will own the technical execution for the AI team. This includes translating high-level user stories into clearly defined technical work packages, creating robust delivery plans in close cooperation with the SW Engineering Team and your own team, and ensuring timely,...

• Design/build AI-ready Lakehouse architectures (Databricks, Fabric) and data pipelines for analytics/ML
• Develop financial data models (Data Vault 2.0) with governance (Purview, Unity Catalog)
• Architect AI infrastructure: Cognitive Search, RAG, vector DBs, knowledge graphs for agentic AI

As a Machine Learning Engineer in our Retail ML team, you will take end‑to‑end ownership of designing, developing and maintaining advanced machine learning solutions that directly influence our commercial performance. Your work will span dynamic pricing, demand forecasting and data‑driven buying...

As a PhD candidate, your tasks will include investigating how foundation models can be effectively applied in industrial reality. To this end, you will develop innovative methods for adaptation, validation, and deployment....

• Design, maintain and deploy scalable, end-to-end training pipelines, including hyperparameter optimization
• Transfer control policies from simulation to real robotic hardware
• Integrate learned policies into a full-stack robotic system, including perception, planning, and actuation

• Shaping AWS-based cloud architectures and technical decisions for SaaS, PaaS, web application, and enterprise cloud environments
• Design and implementation of Infrastructure as Code solutions using Terraform, AWS CloudFormation, or Pulumi