Overview of the job

As an AI Engineer at Sertis, you will play a pivotal role in productionizing advanced data science research. You will be responsible for efficiently running AI models on diverse hardware platforms and architectures, designing and building robust MLOps infrastructure, optimizing models for deployment, and writing production-ready software for model inference. You will work on real-world generative AI use-cases and agentic systems, and collaborate on the development of cutting-edge autonomous, intelligent applications at scale.

In this role, you will get to:

• Collaborate with cross-functional teams to understand business requirements and design ML solutions to meet those needs.
• Develop and maintain scalable infrastructure for model training and deployment.
• Develop cloud-native APIs, pipelines, and general software for model inference.
• Work with cutting-edge foundation models and build agentic systems from scratch
• Troubleshoot and resolve issues related to generative AI models and implementations.
• Engage with clients to gather requirements and ensure smooth collaboration throughout project lifecycles.
• Develop and maintain technical documentation.

You'll be successful if you have:

• At least 2 years of experience as an AI/ML Engineer, past experience in software development and/or machine learning for cloud-based solutions.
• A strong understanding of machine learning processes and standards, as well as the Software Development Life Cycle (SDLC).
• Strong programming skills in Python, C++, or other languages commonly used in machine learning applications.
• Understanding of Generative AI concepts and real-world experience developing Generative AI applications
• Hands-on experience with LLM APIs such as OpenAI or Hugging Face
• An understanding of REST APIs, git version control, CI/CD, and MLOps principles.
• Experience with cloud platforms such as AWS, GCP, or Azure
• Experience with Docker and containerization.
• Excellent problem-solving skills and the ability to work well in a fast-paced, collaborative environment.
• The ability to scope projects, define architectures, and choose technologies based on project requirements.
• Strong communication and interpersonal skills to effectively collaborate with clients and team members.
• Proven experience in providing technical mentorship and guidance to junior engineers.

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