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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.

We are seeking a senior technical leader to serve as Head of AI Engineering for AI Compliance. This role will own the end‑to‑end AI and ML technology strategy, with a strong focus on building and scaling production‑grade ML pipelines for text and voice analysis, risk detection, and classifier training.You will lead the transition from 0 → 1 and beyond: defining architecture, setting engineering standards, and ensuring AI systems are scalable, reliable, secure, and compliant. This role combines hands‑on technical leadership, strategic decision‑making, and team leadership, working closely with product, data science, security, and GTM teams.

• Own the overall architecture for AI and ML systems, including data ingestion, preprocessing, feature engineering, training, evaluation, and deployment.
• Define long‑term technical strategy for text and voice analysis, ML pipelines, and model lifecycle management.
• Make build‑vs‑buy decisions and select core technologies, frameworks, and cloud infrastructure.

• Lead the design and implementation of end‑to‑end ML pipelines from scratch (0 → 1), evolving them into scalable platforms.
• Ensure pipelines support continuous training, evaluation, deployment, and rollback.
• Define standards for data versioning, feature stores, model registries, and reproducibility.

• Oversee data storage, ETL workflows, batch and streaming systems.
• Ensure strong data quality, labeling strategies, lineage, and versioning practices.
• Embed security, privacy, and compliance requirements directly into AI and data infrastructure.

• Drive best practices for production ML: monitoring, drift detection, performance tracking, and retraining strategies.
• Ensure AI systems are fault‑tolerant, observable, and scalable under production workloads.
• Define SLAs, reliability metrics, and incident response processes for ML systems.

• Work closely with Data Scientists and AI Engineers to productionize models (text classifiers, anomaly detection, compliance scoring).
• Partner with Product Management to align AI capabilities with business and customer needs.
• Collaborate with Security and Compliance teams to meet regulatory and governance requirements.

• Build, mentor, and lead high‑performing AI, ML, and data engineering teams.
• Establish engineering culture, best practices, and technical standards.
• Review architecture, provide technical guidance, and unblock complex engineering challenges.

• Ensure thorough documentation of architectures, ETL processes, ML pipelines, and governance frameworks.
• Promote knowledge sharing and long‑term maintainability across teams.

• 6+ years of experience in data engineering, ML engineering, or applied AI roles.
• Proven experience building production ML systems from 0 → 1 and scaling them in real‑world products.
• Experience leading or owning AI platforms in regulated or security‑sensitive environments is a strong plus.
• Prior experience as a technical lead, principal engineer, head of engineering.

• Strong programming background in Python (Scala or Java as additional strengths).
• Deep experience with data processing frameworks such as Spark, Beam, Kafka, or equivalent.
• Strong knowledge of ML frameworks ( PyTorch, TensorFlow, scikit‑learn ).
• Hands‑on experience with cloud‑based data and ML infrastructure.
• Solid understanding of ML lifecycle management, model monitoring, and MLOps practices.

• Strategic thinker with strong system‑design and architectural decision‑making abilities.
• Excellent collaboration and communication skills across technical and non‑technical teams.
• Detail‑oriented, documentation‑driven, and quality‑focused.
• Comfortable balancing hands‑on technical work with executive‑level responsibilities.

• Degree in Data Engineering, Computer Science, Machine Learning, or related field.
• PhD preferred, especially in machine learning, AI, or applied data science.

• Be at the intersection of cutting‑edge AI/voice technology and compliance.
• Make an impact by shaping a growing brand in a high‑growth market.
• Work with a collaborative, high‑energy remote team driving forward‑thinking solutions.
• Grow your career and influence across product, marketing and business domains.