Senior Software Engineer – ML & Data Platforms (m/f/d)

ALM Services Technology Group develops end-to-end Web and Mobile Solutions and works closely with customers usually in long term relations. Founded in 2009 in Poland, ALM opened a branch in Budapest in 2022 and is growing their team in Hungary. The company comprises creative, open-minded individuals who develop innovative solutions daily to help clients expand their businesses. Since 2020, ALM has cooperated with a multinational partner in the med-tech and analytics space, building multiple applications and supporting their growth stages.

• 5+ years experience in Software Engineering, Data Engineering, or Machine Learning Engineering
• Strong commercial experience with Python
• Practical experience with Apache Spark or PySpark
• Experience building production ETL pipelines for ingestion, transformation, validation, enrichment, and delivery
• Experience with ML models or algorithms for entity, identity, or profile matching
• Good understanding of statistics, feature engineering, model evaluation, and data preparation
• Experience with Snowflake, Databricks, or equivalent platforms
• Experience designing and developing microservices and REST APIs
• Practical experience with Azure cloud services
• Knowledge of SQL, data modelling, distributed processing, and large datasets
• Experience with automated testing, CI/CD, version control (GitHub), and code review
• Ability to make architecture decisions and explain technical trade-offs clearly
• Fluent in English

Nice to have:

• MCP
• LLM
• AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or equivalent

• Design, build, and maintain production-grade ETL and data-processing pipelines
• Process large datasets using Python, Apache Spark, PySpark, Snowflake, and Databricks
• Develop entity and profile matching solutions using machine learning, similarity, and graph-based techniques
• Prepare, transform, validate, and enrich data from multiple internal and external sources
• Design data models, matching features, scoring methods, and evaluation strategies
• Build microservices and REST APIs exposing matching and data-processing capabilities
• Improve accuracy, scalability, reliability, and performance of ML and data solutions
• Implement automated tests, data-quality checks, monitoring, and production health checks
• Investigate data issues, matching errors, pipeline failures, and model-quality problems
• Design solutions for reprocessing, backfills, incomplete data, and changing data schemas
• Contribute to system architecture and decision-making related to performance, maintainability, reliability, and cost
• Support CI/CD, code review, deployment, and production operations
• Evaluate practical applications of MCP and agentic AI within the platform
• Collaborate with software, data, machine learning, product, and business teams
• Use AI-assisted development tools while ensuring technical correctness, security, and code quality