Python programmer állások IX. kerületben (it programozás, fejlesztés)

• End-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintenance of CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tuning of complex Spark jobs and LLM inference patterns for performance optimization

• Building transformative AI capabilities from the ground up
• Working with conversational and agentic AI technologies to develop user-facing features
• Experimenting with generative AI models and techniques
• Tackling challenges at the intersection of AI and enterprise software

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn customer data into actionable business value aligned with business goals

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Support Transmission System Operators (TSOs) And Distribution System Operators (DSOs) In Planning The Power Grid Of The Future
• Work Directly With Clients As Part Of International Consulting Project Teams
• Perform Power System Analyses (Power Flow, Voltage, Short‑Circuit, N‑1, Redispatch)

• Development of highly scalable services realizing AI/ML functionalities
• Implementation of machine learning solutions addressing computer vision and NLP use cases
• Work with Large Language Models (LLMs) and perform prompt engineering tasks

• Experience in different Data Science topics
• Independent delivery of Data Science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

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

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Definition and development of system-level tests for high-end embedded computing systems
• Automation of test execution and evaluation through scripting in a CI environment
• Increase of test coverage by extending functional examples into comprehensive test suites

• Design, build, and operate system-level infrastructure for autonomous test vehicles
• Take end-to-end responsibility for components, OS provisioning, deployment and runtime behavior
• Debug complex issues across Linux systems, networking and hardware components

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Collaboration with the Architect in design discussions and proposals
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)

• Cooperation with software teams to establish and implement quality processes at every stage of the development cycle
• Development of automated test cases for firmware and Linux-based systems including bootloaders, kernel, device drivers and applications

• Co-design and implementation of QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Application of AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• Data exploration, profiling, cleansing, and preprocessing
• Design and management of workflows for storing and retrieving vectorised documents
• Application of embedding models to build AI-driven solutions

• Maintaining and evolving AI/ML projects using Python
• Building design Agentic LLM based solutions and maintaining/improving existing ones
• Ensuring output quality by verifying consistency and accuracy
• Investigating, assessing, and developing cloud based MCP solutions

• Design, develop, and maintain C-based applications in Linux/UNIX environments
• Work with system-level interfaces (POSIX APIs, processes, file systems, sockets)
• Develop and enhance Kerberos authentication systems and related tooling

Contribution to and co-leadership of R&D projects exploring novel methods for extracting information from structured, semi-structured, and unstructured data...

• Embedding in the daily life of two engineering teams specialized in AML entity monitoring and case management solutions and device fingerprinting technology
• Ensuring technical design alignment with SEON's architectural best-practices, pragmatism, completeness and precision