AI Engineer (B2B)

Responsibilities

• Support our clients during the successful development and implementation of complex solutions for Data Analytics and Machine learning applications. 
• Through the power of distributed open source and cloud technologies, provide scalable, cost efficient and flexible solutions for our customers. 
• Use your software engineering expertise to provide clean and scalable solutions. 
• Work to iteratively improve and expand machine learning and data driven applications using the latest tools and methodologies in software lifecycle management. 
• Communicate regularly in an efficient and professional manner with our customers and stakeholders 

Qualifications

• We are looking forward to your completed studies in computer science, mathematics, physics, or a similar qualification.
• Programming experience using languages such as Python, Java, and Scala (especially Python).

• Must have experience : 

- Hands-on GenAI use cases and technologies such as Langchain, OpenAI, Bedrock, RAG use cases, multi-agent architectures - at

least 1/2 year of experience.

• Good to have experience areas:

- MLOps frameworks and methodologies (Seldon, Kubeflow, MLflow, Azure or Bedrock tech stack) with at least 1/2 year of

experience.

- Modern development practices (CI/CD, DevOps, GitOps, Agile, etc).

- Cloud (AWS and/or Azure) - at least 1 year of experience.

• Strong analytical and problem-solving skills.
• Very good English skills round off your profile.
• Availability to work in a hybrid mode or remotely with at least 1 visit in the office per quarter.

About Data Reply

Data Reply, as part of the Reply Group, offers a wide range of services to help customers to become data driven. The team is active in various industries and business areas and works closely with clients to enable them to achieve meaningful results through the effective use of data. Data Reply offers many years of experience in transformation projects on the topic of "Data Driven Enterprise". Our experts focus on the development of Streaming and Event-Driven applications, Data Platforms and Machine Learning solutions - automated, efficient and scalable - without compromising IT security.