About the company
Geekhunter is hiring on behalf of our client, a global data & AI consulting company with strong presence in Europe, Asia, and the US.
We are looking for an experienced AI/ML Engineer to design, build, and deploy scalable AI solutions for business and enterprise use cases. This role combines hands-on engineering, technical consulting, cloud architecture, and client-facing collaboration to deliver impactful AI initiatives across Machine Learning, LLMs, and Generative AI.
Key Responsibilities
Solution Engineering
Design, implement, and deploy pragmatic AI solutions (Machine Learning, LLMs, Generative AI) tailored to client business needs.
Develop scalable and production-ready AI systems aligned with business objectives.
Technical Consulting
Act as a technical advisor to client stakeholders.
Translate business requirements into scalable technical architectures and AI solutions.
Guide clients on AI best practices, architecture decisions, and implementation strategies.
Prototyping & Production
Build and validate Proof of Concepts (PoCs).
Transition prototypes into secure, maintainable, and production-ready environments.
Ensure solution performance, scalability, and reliability.
Architecture & Infrastructure
Design robust AI infrastructure using cloud-native services such as AWS, Azure, or GCP.
Build and optimize modern data pipelines and AI deployment architectures.
Collaboration
Work closely with Data Scientists, Project Managers, and Strategy Consultants to ensure successful delivery of AI initiatives.
Support cross-functional collaboration throughout project execution.
Mentorship
Lead technical workstreams and mentor junior engineers.
Promote engineering best practices, coding standards, and MLOps principles.
Experience
Minimum 3 years of experience in Software Engineering, Data Science, or AI/ML development.
Core Programming
Strong proficiency in Python and SQL.
Experience with Java, C++, or Node.js is a plus.
AI/ML Frameworks
Hands-on experience with TensorFlow, PyTorch, or HuggingFace.
Generative AI
Experience working with LLMs, prompt engineering, fine-tuning, and vector embeddings.
Cloud Platforms
Proven experience deploying AI solutions on AWS, GCP, or Azure.
Tools & DevOps
Proficiency with Git, Docker, Kubernetes, and MLOps practices.
Understanding of CI/CD pipelines for machine learning deployment.
Data Engineering
Experience building and managing ETL/ELT pipelines.
Familiarity with SQL, NoSQL, and Graph database architectures.
Qualification & Soft Skills
Education
Communication
Fluent in English and the local regional language (German or French).
Strong ability to communicate complex technical concepts to non-technical stakeholders.
Mindset
Builder mindset with the agility to work in a fast-paced and client-facing consulting environment.
Consulting Experience
Previous experience in a consulting or professional services company is highly preferred.