Solution Architect

Job Description

As a technical lead at Machine Learning Architects, you take responsibility for both team-internal as well as customer projects. With your hands-on mentality, you will contribute to the development of our cell by mentoring other engineers and develop solutions that enable companies to start and complete their machine learning journey successfully.

Role & Responsibilities

  • Consulting & Training: To help our clients master the challenges of the digital transformation and help them understand the full potential of data science and machine learning.
  • Operationalizing ML by successfully executing data and machine learning projects from prototyping to the deployment of production-ready systems. This includes implementing concepts such as traceability, scalability, measurability, and automation within demanding projects and technology environments.
  • Development of our services by creating solution blueprints for our value propositions, e.g. lead technical responsibility for our “Digital Highway” concept for Machine Learning systems.
  • Business development: Support us in positioning our offer on the market. This includes the preparation and presentation of our offers to potential clients (pre-sales).
  • Lead responsibility for analyzing customer requirements by designing and building system architectures for customer-specific solutions.
  • Be a trusted advisor for our clients.
  • Evaluate and benchmark cutting-edge machine learning technologies to enable our team supporting customers with the best solution for their requirements.
  • Mentor other architects and engineers and help develop young talents.

Your Qualifications & Experiences

  • You are a tech polyglot with cross-functional expertise in the field of data and system architectures.
  • At least 5 years of experience in designing and implementing enterprise systems.
  • Solid domain knowledge in at least one industry (ideally pharma or finance).
  • Solid software architecture skills in both cloud and on-premises with experience in defining customer solutions with Azure, AWS, or Google Cloud.
  • Experienced in communicating with various technical and non-technical stakeholders including management.
  • You understand and are skilled in navigating the complex interactions of data science, machine learning, and DevOps.
  • You are motivated to quickly master the 4 Cs of “MLOps” for Machine Learning systems to design, build and manage data, model and code pipelines: Continuous Integration (CI), Continuous Delivery (CD), Continuous Training (CT), Continuous Monitoring (CM).


Basel, Switzerland

Start Time