ML Engineer H/F

11 months ago

Remote, Worldwide +3 moreAny Level

Responsibilities

Design and develop scalable AI/ML architectures in public cloud environments.
Integrate AI/ML models into existing applications.
Build and optimize MLOps pipelines to industrialize machine-learning models.
Implement generative-AI solutions involving LLMs, RAG, and vector databases.
Deploy customized or managed models.
Collaborate with Data Science, Data Engineering, DevOps, and business teams.
Monitor technology developments and raise clients’ awareness of the ethical and legal considerations of AI.

Experience or capability in machine-learning engineering, AI/ML architecture, model deployment, and MLOps.
Ability to work with public-cloud platforms and AI/ML services including AWS, GCP, Azure, SageMaker, Bedrock, and Vertex AI.
Ability to develop generative-AI solutions using LLMs, RAG, and vector databases.
Knowledge of Python and the listed application-development, orchestration, containerization, and deployment technologies.
Ability to collaborate with multidisciplinary technical and business teams and advise clients on AI topics.

Work with a collaborative team where employees can contribute their own ideas.
Personalized follow-up with a technical manager who understands the profession.
Personalized career progression, including opportunities for increased responsibility, tutoring, technical management, and speaking.
Continuous training and certifications through the BlackBelt program, including AWS, GCP, and Azure mentoring and coaching.

501-1,000 employees