Overview of the job
As an AI Engineer Lead at Sertis, you will lead a team of AI engineers, focusing on productionizing advanced data science, managing model deployment on diverse hardware, designing MLOps infrastructure, and optimizing models. Your role involves developing scalable autonomous and intelligent applications, writing production-ready software for model inference, and working on real-world generative AI and agentic systems. You will foster a high-performing team through continuous feedback and performance reviews.
In this role, you will get to:
- Lead and mentor a team of AI engineers, fostering their professional growth and technical skills.
- Strategically plan and execute AI initiatives by managing project roadmaps, resource allocation, and setting clear, data-driven goals.
- Conduct regular performance reviews and provide continuous, constructive feedback to ensure team success and individual development.
- 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:
- 3+ years of experience as an AI/ML Engineer with a background in software development and/or machine learning for cloud-based solutions.
- 2+ years of experience in a technical team lead or management role.
- 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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