- Company Name
- ERBA DIAGNOSTICS FRANCE
- Job Title
- Data & AI Engineer F/H
- Job Description
-
Job title: Data & AI Engineer (M/F)
Role Summary:
Design, build, and integrate AI/ML models, data pipelines, and intelligent agents into products and internal tools. Leverage data engineering, statistical analysis, and signal/image processing to deliver pragmatic, solution‑oriented outcomes across multidisciplinary teams, while driving continuous innovation in emerging AI technologies.
Expectations:
• Deliver end‑to‑end AI solutions that meet performance and reliability standards.
• Communicate technical results clearly to non‑technical stakeholders and provide training on new tools.
• Maintain rigorous testing, validation, and documentation of algorithms.
• Stay current with state‑of‑the‑art AI frameworks, APIs, and best practices, and translate them into business‑value use cases.
Key Responsibilities:
1. Data Science & Algorithm Development
– Collect, cleanse, and transform data via automated pipelines.
– Apply statistical, signal, or image processing techniques to extract actionable insights.
– Build, optimize, and maintain supervised/unsupervised ML models (classification, regression, NLP, vision, random forest, deep learning).
– Design test plans, evaluate algorithm performance, and validate results.
– Produce technical reports and internal presentations.
2. AI Engineering & Internal Tools
– Create IA solutions such as automated summaries, writing assistants, business assistants, document/analysis automation.
– Develop autonomous AI agents that plan, reason, and execute business actions.
– Orchestrate multi‑agent workflows to address complex needs.
– Integrate tools into corporate environments and support deployment.
3. Innovation & Continuous Improvement
– Explore, prototype, and test novel AI/ML solutions, APIs, and frameworks.
– Recommend new AI/data applications aligned with business, R&D, and operations.
– Simplify and industrialize solutions for practical, scalable impact.
– Conduct active knowledge monitoring in AI, data engineering, and data management.
4. Support & Cross‑Functional Collaboration
– Train colleagues on AI/data tools and best practices.
– Host workshops, create documentation, and drive adoption.
– Work closely with software, hardware, electronics, biology, quality, and operations teams.
– Translate complex technical concepts into accessible insights.
Required Skills:
- Proficiency in Python and/or C#; solid coding and version control.
- Strong foundation in machine‑learning techniques (classification, regression, NLP, computer vision, random forest, modern deep‑learning models).
- Adept with statistical analysis, signal/image processing.
- Experienced with data‑engineering pipelines and best practices (ETL, data lakes, data warehouses).
- Familiar with current AI tools/technologies (LLMs, agent frameworks, APIs).
- Excellent written and verbal English (professional level).
- Strong analytical mindset, problem‑solving, and the ability to innovate pragmatically.
- Effective communication, documentation, and teamwork across diverse disciplines.
Required Education & Certifications:
- Engineering degree, Master’s, or Ph.D. in Data Science, Computer Science, Statistics, Applied Mathematics, or related field.
- Relevant certifications in AI/ML or data engineering (e.g., TensorFlow, PyTorch, AWS SageMaker, GCP AI, or equivalent) are a plus.