Head of AI Engineering – AI Compliance
All Seniors Care Living Centres
full-time
Posted on:
Location Type: Remote
Location: France
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Job Level
About the role
- 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
- 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
- Build, mentor, and lead high-performing AI, ML, and data engineering teams
Requirements
- 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
- Degree in Data Engineering, Computer Science, Machine Learning, or related field
- PhD preferred, especially in machine learning, AI, or applied data science
Benefits
- Work with a collaborative, high-energy remote team driving forward-thinking solutions
- Grow your career and influence across product, marketing and business domains
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data engineeringML engineeringapplied AIPythonScalaJavaSparkBeamKafkaPyTorch
Soft skills
leadershipmentoringteam buildingstrategic planningproblem solvingcommunicationcollaborationdecision makingproject managementbest practices
Certifications
PhD in machine learningPhD in AIPhD in applied data science