Python állások XIV. kerületben (ai és automatizáció)

• 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

• Architect and lead the development of large-scale ML systems and model pipelines
• Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
• Define and drive the ML technical roadmap in alignment with company objectives

• Build and maintain simulation environments for mobile robotic perception and navigation
• Develop and integrate robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

• Designing and developing new machine learning models with a focus on real-time performance
• Integrating cutting-edge ML features into the SkeleTRACK product
• Analysing model performance and identifying areas of improvement
• Mentoring junior engineers and driving technical discussions

• Delivery of complex data engineering projects across industries
• Leading small delivery teams
• Management of customer relationships alone or with a Project Manager
• Supporting pre-sales process
• Mentoring more junior engineers
• Contributing to hiring best-in-class data talent

Ready to fast‑track your career and take on real global challenges? ...

• Chunking and ingestion architecture with deterministic, validation-gated pipelines handling diverse enterprise document types with indexing and contextual enrichment
• Retrieval pipeline with vector search, BM25 hybrid retrieval, RRF re-ranking, embedding model selection and optimisation

• Development of the Voice AI Agent using Python, LiveKit and WebRTC
• Ownership of end-to-end real-time voice pipelines including streaming ASR/TTS, VAD, diarization, state management, retries and latency optimization

• Design and implement automated test cases for backend, frontend, or API-based systems
• Collaborate with distributed teams across multiple time zones
• Participate in requirement analysis to ensure testability and clarity

Performing tasks related to the position....

• Design and ship production-grade agentic systems
• Take technical ownership of Compliance in a Box (CiaB) AI platform
• Architect and evolve AI reasoning layer and agent orchestration framework
• Build and maintain the GRC Brain (AI reasoning layer) and Agentic Cortex (agent orchestration framework)

• 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

• Design and implement new market links and connectivity tools
• Improve and maintain existing high-load, low-latency C++ applications
• Actively reduce latency to optimize trading performance
• Ensure operational excellence and reliability of systems as they scale

• Design and implement new market links and connectivity tools
• Improve and maintain existing high-load, low-latency C++ applications
• Actively reduce latency to optimize trading performance
• Ensure operational excellence and reliability of systems as they scale

• Definition and improvement of metrics representing product performance and operations efficiency
• Data collection from multiple sources ensuring accuracy and completeness
• Data cleaning, organization, and transformation into usable formats for analysis

• Build-from-zero applications powered by the HawkAI Engine
• Bridge machine learning models and real-time data pipelines into APIs and user interfaces
• Integrate AI-assisted development tools into software architecture and data integrity workflows

Strukturált workshopok és munkamegbeszélések vezetése végfelhasználókkal annak megértése érdekében, hogy a folyamatok a gyakorlatban hogyan működnek, beleértve a kivételeket, manuális kerülőmegoldásokat és a nem dokumentált döntési szabályokat is....

• Design and evolve robust cloud-native services and platforms with end-to-end ownership from ideation and prototyping to deployment, monitoring, and iteration
• Influence technical direction without direct authority by identifying architectural pain points and improving engineering standards

• Contribution to the ID Verification ML team building in-house ML solutions
• Delivery of high-quality NodeJS, TypeScript and Python code with simplicity, performance and scalability in mind

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása