ML/Data Engineer

This is a fully remote position, open to applicants in Romania, +5 more countries.

📋 Description

• Design and construct production data infrastructure for high-volume athlete performance and sensor data.

• Develop and manage real-time and near-real-time ingestion systems for streaming data.

• Architect storage and data structures for high-volume time-series data and longitudinal athlete records.

• Create infrastructure that delivers production features and derived metrics to machine learning systems and AI agents with minimal latency.

• Formulate and implement graph data models and schemas that illustrate relationships among athletes, training loads, injuries, performance, and outcomes.

• Establish data and machine learning evaluation infrastructure that aids in assessing model reliability, calibration, and performance in real-world scenarios.

• Design systems that ensure strong tenant-level data isolation across clubs and clients.

• Implement appropriate data provenance, lineage, auditability, and observability throughout the platform.

• Collaborate with ML and AI engineers to furnish dependable data foundations for model training, inference, and evaluation.

• Partner with sport scientists and domain experts to convert intricate requirements into robust production systems.

• Make informed technology and architecture decisions as the platform continues to evolve.

• Work in partnership with Intetics Inc.'s client in the USA.

⛳️ Requirements

• Over 5 years of full-time professional experience in software or data engineering, excluding internships, university placements, coursework, and academic projects.

• Demonstrated experience in designing, constructing, and managing production data infrastructure at scale.

• Strong background in working with time-series data or time-series databases, such as InfluxDB, TimescaleDB, Prometheus, ClickHouse, or comparable technologies.

• Extensive experience in real-time or streaming data ingestion, utilizing technologies such as Kafka, Kinesis, Flink, Spark Streaming, Pulsar, or similar.

• Proven experience in designing graph data models or graph database schemas, rather than merely querying or utilizing an existing graph database.

• Experience in designing or managing multi-tenant systems with tenant-level data isolation.

• Proficient in Python and SQL.

• Professional experience with Go is highly advantageous.

• Experience with production systems where reliability, scalability, observability, and data correctness are critical.

• Capability to take ownership of ambiguous technical issues and transform them into practical production architectures.

• Experience collaborating directly with data scientists, ML engineers, or other technical domain specialists.

• Familiarity with building probabilistic evaluation, model calibration, or model monitoring infrastructure.

• Experience with causal inference, counterfactual modeling, or simulation.

• Experience with wearable sensors, IoT data, biomechanics, sports technology, or other high-frequency telemetry.

• Expertise in building knowledge graphs or domain-specific ontologies.

• Knowledge of LLM or AI evaluation frameworks and an understanding of their limitations.

• Experience with AWS services, including ECS, EC2, Lambda, SNS, SQS, or similar offerings.

• Familiarity with GraphQL, REST, gRPC, Postgres, MongoDB, or comparable technologies.

• Proficiency in English at a B2+ level.

• Candidates must reside in the EU.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Flexible working hours with opportunities for remote work.

• Access to professional development and training resources.

• Collaborative and innovative work environment.

• Health and wellness benefits.