Python programmer állások Budapesten (it programozás, fejlesztés)

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices

• Co-design and implement 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

• Identify AI and automation opportunities across business processes
• Work with different departments to understand processes, pain points and repetitive activities
• Challenge existing ways of working and propose simpler, automated or completely new approaches

• Be able to manage small teams to deliver analytic functions in support of strategic and business development projects.
• Analyse and assess macroeconomic, energy market and other industry-specific developments by synthetizing available empirical evidence, related literature, and economic theory.

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Solution design and delivery
• Design and configuration of data labeling and processing pipelines using Python-based tools

• 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

• részvétel a teljes egyetemi adatvagyon központosítását célzó, az egyetem által működtetett adattárház továbbfejlesztésében,
• adattisztítás módszertanának fejlesztése, adatmodellek létrehozása, adatkapcsolatok kialakítása, sématervezés,

• Development, governance, deployment, and ongoing enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle including prioritizing initiatives, influencing roadmap decisions, and ensuring successful deployment into production

• Vállalati szintű adatfeldolgozó (ETL/ELT) folyamatok tervezése és megvalósítása
• Adatintegrációs megoldások fejlesztése heterogén rendszerek között
• Adatmodellek kialakítása, optimalizálása és dokumentálása
• Adatminőségi kontrollok és monitoring mechanizmusok implementálása

• 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

• Managing complex database systems within a global technology ecosystem
• Building and managing database hosting capabilities using Infrastructure as Code for all platform needs
• Building database infrastructure platforms with developers and providing guidance and tooling to handle distributed systems

• 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

Performing tasks related to the position....

• Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
• Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
• Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect

• collaborating on the design and development of ML‑based applications and their backend components
• helping to select the most applicable solutions for a given business problem
• writing clean, efficient and well‑documented code
• contributing to our MLOps processes

• 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

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...

• 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