About the CompanyCephalgo 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. Role SummaryWe are looking for a Senior / Principal AI Engineer to design, build, and scale applied AI systems for text and voice analysis, with a strong emphasis on time-series and sequential data.

You will own models end-to-end — from data understanding and experimentation to production deployment — working on real-world time-dependent signals such as voice streams, sessions, and evolving sequences.

This is not a pure MLOps role.

Infrastructure exists to support high-quality modeling, fast iteration, and reliable deployment — not to replace applied AI ownership.

What You’ll Work OnApplied AI Modeling (Core Focus)Design, train, and evaluate ML models for text and voice analysis. Work on time-series and sequential modeling problems. Own feature engineering, labeling strategies, and evaluation metrics.

Iterate on models based on real-world data and performance feedback. ML Pipelines Production SystemsBuild and evolve ML pipelines that support experimentation and continuous improvement. Deploy models into production and ensure performance, scalability, and stability. Implement model monitoring and retraining workflows. Time-Series Sequential DataAnalyze and model time-dependent data such as voice signals, sessions, and event sequences. Apply time-aware techniques (windowing, aggregation, decay, sequence modeling). Improve model behavior as data distributions evolve over time. Data Platform CollaborationCollaborate with data engineering teams on ETL, data quality, and data versioning. Contribute to architecture decisions around feature stores and model registries. Technical LeadershipInfluence modeling approaches and technical direction across the product. Mentor engineers and raise engineering and modeling standards. Work closely with product teams to translate

requirements

into effective AI solutions.

What This Role Is (and Is Not)This role is:applied AI and modeling-firsttime-series focused

Product

ion-oriented with ownershipThis role is not:pure MLOpsinfra-only or DevOps-heavyresearch-only with no product impact

Qualifications

Experience5+ years in AI Engineering, Applied Machine Learning, or similar roles. Proven experience building and owning production ML models. Experience working with text, speech, or other unstructured data. Technical SkillsStrong programming skills in Python. Experience with PyTorch, TensorFlow, or scikit-learn. Solid understanding of time-series or sequential modeling techniques. Familiarity with ML pipelines and production deployment. Nice-to-HaveExperience with streaming or near-real-time data. Exposure to Spark, Kafka, or similar data frameworks. Experience working with voice or audio data. Soft SkillsStrong analytical and problem-solving abilities. Comfortable owning systems end-to-end. Clear communicator who collaborates well across teams. EducationDegree in Computer Science, Machine Learning, Data Engineering, or related field. Advanced degrees are a plus, but practical experience is key. ‍.