What you’ll do

Craft.AI combines a product - its Data Science and MLOps platform - with AI expertise to develop and deploy at scale AI solutions for business and industrial needs.

We are actively looking for an AI architect to frame and define AI solutions from the ideation stages to the project specification, including the definition of the use case approach and the validation of prospect’s data assets. In various fields such as Greentech, energy, health or education, you will design and elaborate AI solutions in presales phases.

The proposed collaborative role is at the nexus of the Data Science team and the Sales department. Through the connection with prospects and market needs, you will also contribute to refine the business model and suggest evolutions to the Product team.

As part of the Data Science team, you will thus collaborate to:

• Identify the needs and expectations of potential customers in collaboration with the Sales team,
• Provide technical expertise to frame and define prospective AI architectures in order to transform business issues into an in-production solution hosted by the Craft.AI MLOps platform : use case cracking, AI approach and IT integration,
• Evaluate the cost, benefits and ROI for prospects of Craft.AI solution deployments,
• Advocate AI solutions and the industrialization of Machine Learning on events and to the Data community,
• Advise the Product team on market needs and collaborate to the product roadmap definition.

Experience:

• You have a master or PhD degree,
• With a minimum of 3 years of experience in Consulting firms or in the Industry,
• You have been involved into several data-centric projects,
• You know the fondamentals of ML/AI methods.

Skills:

• Good speaker that is eager to understand business systems and needs,
• A strong taste for AI and its current developments,
• Entrepreneurial attitude, willing to evolve in a startup environment,
• Organized and curious,
• Fluent in French and solid in English.

Three stages, usually done in 10 days:

• Non-technical discussion with the Head of Data Science
• Interview with the VP Sales
• Interview around a business case and discussion with the existing Presales / AI Architect.

One on-site interview at least is expected along the recruitment process.