German-Speaking AI & MLOps Consultant

Machine Learning Architects Basel (MLAB); Basel; Hybrid; CHF 120.000 - 160.000; Vollzeit

Benefits dieser Stelle

Hybrid working model

Knowledge-sharing sessions

Team events

Impactful projects

Zusammenfassung

Machine Learning Architects Basel (MLAB) seeks an experienced AI & MLOps Engineering Consultant to drive the full project lifecycle, collaborating with clients and internal teams to design and operationalize data and ML solutions.

You will analyze requirements, implement data pipelines, ML/LLM integrations, reliability engineering, and contribute to blueprint development, while sharing knowledge and guiding stakeholders.

Qualifikationen

• Minimum 3 years of professional experience in ML/AI or software engineering focusing on data and ML systems.
• Experience with major data & AI platforms (e.g., Snowflake, Databricks, Dataiku, IBM Watson).
• Familiarity with DataOps, DevOps, MLOps, Data Mesh, Data Lake/Warehouses, and reliability engineering.
• Familiarity with data engineering, ML, and Generative AI models, frameworks & tools.
• Strong understanding of end-to-end project lifecycles and stakeholder collaboration.

Aufgaben

• Consulting, Engineering & Training: translate data/ML engineering into valuable client offerings.
• Requirement Analysis: identify best-fit solutions for customer needs.
• Implementation of Data Pipelines, ML/LLM Integrations, Reliability Engineering & AI/ML Operationalization: deliver production-ready systems.
• Concept Development: contribute to solution blueprints and patterns.
• Expertise & Thought Leadership: own work, present results, share knowledge, and collaborate with teams.

Kenntnisse

German & English fluency

Client-facing experience

AI engineering concepts

MLOps & Data pipelines

Tools

Snowflake

Databricks

Dataiku

IBM Watson

Docker

Kubernetes

Hadoop

Spark

SQL

NoSQL

REST API

CI/CD

Jobbeschreibung

Machine Learning Architects Basel (MLAB) seeks an experienced AI & MLOps Engineering Consultant to drive the full project lifecycle, collaborating with clients and internal teams to design and operationalize data and ML solutions.

You will analyze requirements, implement data pipelines, ML/LLM integrations, reliability engineering, and contribute to blueprint development, while sharing knowledge and guiding stakeholders.