Sertis - Machine Learning Engineer/AI Engineer
Requirements
• At least 3 years of experience as an AI/ML Engineer, past experience in Data science, Software development and/or Machine learning for cloud-based solutions. • At least 3 years of experience as an AI/ML Engineer, • A strong understanding of machine learning processes and standards, as well as the Software Development Life Cycle (SDLC). • strong understanding of machine learning processes and standards • Strong programming skills in Python, C++, or other languages commonly used in machine learning applications. • Good understanding of Generative AI concepts and real-world experience developing Generative AI applications • Good understanding of Generative AI concepts • 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. • REST APIs, • Experience with cloud platforms such as AWS, GCP, or Azure • 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. • Strong communication skills in English • Sertis may collect, use, or disclose your personal data or personal data of other persons provided by you in order to carry out your recruitment process. For more information, please refer to our Recruitment Privacy Notice#LI-SERTIS • #LI-SERTIS
Responsibilities
• Collaborate with cross-functional teams to understand business requirements and design ML solutions to meet those needs. • design ML • Develop and maintain scalable infrastructure for model training and deployment. • Develop and maintain scalable infrastructure • Develop cloud-native APIs, pipelines, and general software for model inference. • Develop cloud-native APIs, pipelines • Work with cutting-edge foundation models and build agentic systems from scratch • 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.
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