AI Engineer

Cephalgo is a Strasbourg-based technology company founded in 2020, focused on developing AI solutions that ensure safety, compliance, and trust in human-AI interactions. Originally rooted in healthcare innovation, Cephalgo's platform helps organizations securely analyze and monitor voice and emotion data while meeting privacy, security, and regulatory standards.

Backed by over €3 million in funding, Cephalgo combines deep expertise in voice AI, data protection, and compliance frameworks to help enterprises build and deploy responsible AI systems. The company collaborates with leading European partners in AI ethics, healthcare, and regulatory technology.

An AI Engineer with strong ML pipeline experience to build and scale systems for text and voice analysis, risk detection, and classifier training. You will develop production-grade pipelines from 0 → 1 and support machine learning initiatives across the product.

Pipeline Development

• Build and maintain end-to-end ML pipelines: data ingestion, preprocessing, feature extraction, model training, evaluation, and deployment.
• Develop reliable workflows for voice and text analysis models.

Data Infrastructure

• Design and maintain data storage, ETL workflows, and streaming/batch systems.
• Implement data quality, labeling, and versioning practices.

ML Collaboration

• Work with data scientist and AI engineer to productionize models (text classifiers, anomaly detection models, compliance scoring models).
• Support model monitoring and performance tracking.

Scalability & Reliability

• Build robust, scalable, and fault-tolerant pipelines.
• Add observability layers: logging, monitoring, alerting.

Documentation & Governance

• Document ETL processes, schemas, and architecture.
• Support compliance, data governance, and security standards.

Experience

• 3+ years in data engineering or ML engineering.
• Proven experience building ML pipelines from scratch.
• Experience with text classification or similar ML tasks.

Technical Skills

• Strong programming skills (Python, Scala, or Java).
• Experience with Spark, Beam, Kafka, or similar frameworks.
• Familiarity with ML frameworks (PyTorch, TensorFlow, scikit-learn).
• Experience with cloud data infrastructure.

Soft Skills

• Strong analytical and collaboration skills.
• Detail-oriented and documentation-focused.

Education

• Degree in Data Engineering, Computer Science, Machine Learning, or similar field. PhD degree is preferred.