ML/Data Engineer

🔥 1 hour ago

🌐 Romania, Bulgaria, +4 more countries – Remote

🇷🇴 Romania – Remote 🇧🇬 Bulgaria – Remote 🇵🇹 Portugal – Remote 🇵🇱 Poland – Remote 🇸🇰 Slovakia – Remote 🇪🇸 Spain – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Intetics

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1995

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Intetics is an innovative company providing custom software development services, specializing in AI and machine learning solutions. They offer Remote In-Sourcing® to build expert teams for software engineering and data processing projects, along with advanced tools like TETRA™ for software quality assessment. Intetics aims to empower businesses by leveraging high-quality data and integrating modern technologies across various industries, including healthcare, finance, and more.

📋 Description

• Design and build production data infrastructure for high-volume athlete performance and sensor data. • Build and operate real-time and near-real-time ingestion systems for streaming data. • Design storage and data architectures for high-volume time-series data and longitudinal athlete records. • Build infrastructure that makes production features and derived metrics available to machine learning systems and AI agents with low latency. • Design and implement graph data models and schemas representing relationships between athletes, training loads, injuries, performance, and outcomes. • Build data and ML evaluation infrastructure that helps measure model reliability, calibration, and performance across real-world cases. • Design systems that maintain strong tenant-level data isolation across clubs and customers. • Establish appropriate data provenance, lineage, auditability, and observability across the platform. • Work with ML and AI engineers to provide reliable data foundations for model training, inference, and evaluation. • Work with sport scientists and domain experts to translate complex requirements into durable production systems. • Make pragmatic technology and architecture decisions as the platform evolves. • Collaborate with Intetics Inc.'s customer in the USA.

🎯 Requirements

• 5+ years of full-time professional software or data engineering experience, excluding internships, university placements, coursework, and academic projects. • Proven experience designing, building, and operating production data infrastructure at scale. • Strong experience working with time-series data or time-series databases, such as InfluxDB, TimescaleDB, Prometheus, ClickHouse, or equivalent technologies. • Significant experience with real-time or streaming data ingestion, using technologies such as Kafka, Kinesis, Flink, Spark Streaming, Pulsar, or equivalent. • Experience designing graph data models or graph database schemas, not simply querying or consuming an existing graph database. • Experience designing or operating multi-tenant systems with tenant-level data isolation. • Strong Python and SQL skills. • Professional experience with Go is highly desirable. • Experience working with production systems where reliability, scalability, observability, and data correctness matter. • Ability to take ownership of ambiguous technical problems and turn them into practical production architectures. • Experience working directly with data scientists, ML engineers, or other technical domain specialists. • Experience building probabilistic evaluation, model calibration, or model monitoring infrastructure. • Experience with causal inference, counterfactual modelling, or simulation. • Experience working with wearable sensors, IoT data, biomechanics, sports technology, or other high-frequency telemetry. • Experience building knowledge graphs or domain-specific ontologies. • Experience with LLM or AI evaluation frameworks and an understanding of their limitations. • Experience with AWS, including ECS, EC2, Lambda, SNS, SQS, or related services. • Experience with GraphQL, REST, gRPC, Postgres, MongoDB, or similar technologies. • English B2+ language proficiency. • Candidate must be located in the EU.