Senior AI Engineer / Data Scientist (Machine Learning/python)

We are seeking a highly skilled and experienced Senior AI Engineer / Data Scientist to join our dynamic group. In this pivotal role, you will be responsible for designing, developing, and implementing cutting-edge (Generative) AI solutions leveraging Python, Machine Learning, Large Language Models (LLMs), and classical Natural Language Processing (NLP) methodologies. You will collaborate closely with two expert teams to analyze large datasets, build robust models, and create innovative solutions. Additionally, you will play a key role in guiding junior colleagues and may take on topic leadership for specific areas.

This position demands a high degree of adaptability and willingness to contribute to both short-term, agile projects and longer-term strategic developments, such as an in-house developed chat system. Your contribution will be crucial in ensuring we always have up-to-date and demonstrable solutions readily available for pre-sales activities and rapid prototyping.

Key Responsibilities:

• Design & Development: Design, develop, and implement advanced machine learning algorithms, models, and LLM-based pipelines.

• Data Analysis & Insights: Analyze large datasets to extract meaningful insights and patterns.

• Software Engineering: Write production-quality code in Python, adhering to standard software engineering best practices (Git, testing, etc.). A strong focus will be on backend development using FastAPI and leveraging Azure SDKs. Support basic front-end development tasks.

• Collaboration & Problem Solving: Collaborate effectively with cross-functional teams to identify, understand, and solve complex business problems.

• Technology Adoption: Stay up to date with the latest advancements in AI, GenAI, and data science, actively integrating new technologies where beneficial.

• Integration & Deployment: Work closely with software engineers to integrate AI models into production systems and package AI components for reusability.

• Mentorship & Leadership: Provide guidance and mentorship to junior data scientists and engineers, potentially leading specific topics or initiatives.

• MLOps & Infrastructure: Contribute to the development of robust MLOps pipelines (CI/CD for ML) and apply strong skills in Docker and container orchestration.

• Strategic Evaluation: Research and evaluate external AI services versus in-house development ("Make or Buy") in a global context, assessing feasibility and ROI.

• Agile Contribution: Support highly volatile projects on demand and contribute to rapid prototyping and continuous improvement. Develop use cases and demos for pre-sales purposes, ensuring consistently updated versions.

Mandatory Qualification

1. Academic Background: At least a Bachelor's degree in Computer Science, Data Science, or a related field.

2. Experience: Minimum of 5 years of experience in data science and AI engineering.

Software development: Strong proficiency in Python (backend development with FastAPI, Azure SDKs/Libraries/APIs).

3. Machine Learning & Deep Learning:

- In-depth knowledge of machine learning algorithms and techniques.

- Proficiency in common machine learning frameworks (e.g., TensorFlow, PyTorch).

4. LLMs & NLP:

- Extensive experience with Large Language Models (LLMs) like GPT, BERT, Claude.

- Experience with RAG or agent frameworks (e.g., Langchain, LLamaIndex).

- Basic skills in Natural Language Processing (NLP) techniques and libraries.

5. Cloud Environment: Familiarity with Azure & Enterprise IaaS / PaaS, with a strong focus on the Azure EcoSystem.

6. Data Storage & Vector Stores: Interaction with Azure Tables and Qdrant Vector Store.

7. DevOps/MLOps:

- Strong Docker skills and experience with container orchestration.

- Experience with MLOps (CI/CD for ML).

8. Problem-Solving & Analytical: Strong problem-solving and analytical skills.

9. Communication:

- Excellent communication and collaboration abilities.

- Clear and proactive communication skills, emphasizing transparency.

- Fluent in English (written and verbal).

- Ability to convey complex technical topics to non-technical stakeholders.

10. Teamwork & Initiative:

- Ability to work independently and strong motivation to integrate into and shape an international team environment.

- Experience working with distributed teams and adapting to time zone differences.

- Proven experience with remote collaboration tools.

11. Work Ethic:

- Strong attention to detail and ability to plan and prioritize tasks.

- Constructive feedback culture.

- Iterative development, rapid prototyping, continuous improvement.

- Flexibility to adapt to changing requirements.

12. Intercultural Competence: Respect for cultural differences and international business protocols.

13. Continuous Learning: Openness to continuous learning and integration into company structures.

14. Business Acumen: Ability to quick assessment of feasibility and ROI.

Nice-to-Have Qualification

- Proficiency in NodeJS.

- Basic skills in front-end development.

- Ability to adapt to other cloud platforms (AWS, GCP) if needed.

- Basic experience in infrastructure automation (e.g., Terraform) is a plus.

- Ability to package AI components for reusability.