ML/Data Engineer (AI)

Location: Remote, hybrid, or office-based work is available in Albania, Belgium, Bulgaria, Canada, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Italy, Latvia, Lithuania, Luxembourg, Montenegro, North Macedonia, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, the Netherlands, Turkey, or the USA.

Salary: EUR 3,050–5,000 gross per month. Additional annual bonus participation can provide up to EUR 1,000 per month depending on expertise.

Company

hirify.global delivers software platforms and data-driven solutions for international clients across industries including fintech, healthcare, retail, and telecommunications.

What you will do

• Design and operate production data infrastructure for high-volume athlete performance, sensor, and time-series data.
• Build real-time and near-real-time streaming ingestion systems.
• Design storage architectures and graph data models for athletes, training loads, injuries, performance, and outcomes.
• Provide low-latency production features and derived metrics for machine learning systems and AI agents.
• Build data and ML evaluation infrastructure for reliability, calibration, and performance measurement.
• Establish tenant-level data isolation, data provenance, lineage, auditability, and observability while collaborating with ML engineers and sports scientists.

Requirements

• 5+ years of professional software or data engineering experience, excluding internships and academic projects.
• Experience designing, building, and operating production data infrastructure at scale.
• Strong experience with time-series data or databases such as InfluxDB, TimescaleDB, Prometheus, or ClickHouse.
• Significant experience with streaming technologies such as Kafka, Kinesis, Flink, Spark Streaming, or Pulsar.
• Experience designing graph data models, multi-tenant systems, and tenant-level data isolation.
• Strong Python and SQL skills, production reliability experience, and Upper-Intermediate+ English.

Nice to have

• Professional experience with Go.
• Experience with model calibration, probabilistic evaluation, causal inference, simulation, or ML monitoring.
• Knowledge of wearable sensors, IoT telemetry, biomechanics, sports technology, knowledge graphs, or domain ontologies.
• Experience with LLM evaluation frameworks, AWS, GraphQL, REST, gRPC, Postgres, or MongoDB.

Culture & Benefits

• Remote, hybrid, and office-based work options are available.
• Mentoring, onboarding support, professional development, and access to a corporate training portal.
• Certification compensation, referral program, and opportunities to change projects or develop domain expertise.
• Private health insurance and sports compensation may be available depending on the employment type.
• Corporate social activities and team events are provided.