HOW YOU WILL CONTRIBUTE AND WHAT YOU WILL LEARN
- Architect and develop AI/ML use cases on Cloud, driving projects from discovery and proof of concept through industrialization, deployment, and ongoing maintenance.
- Mentor and guide junior engineers in defining robust methodologies and evaluating the most effective technical solutions.
- Propose, implement, test, and select optimal machine learning algorithms by leveraging advanced statistical tools and data science techniques to uncover insights and generate accurate predictions.
- Drive the rapid scaling and integration of AI and ML technologies to enhance system performance and support strategic business objectives.
KEY SKILLS AND EXPERIENCE
You have:
- Bachelor’s or master’s degree in computer science, Engineering, or related field with 8+ years of experience in machine learning, data science, and statistics.
- Expertise in ML algorithms with strong Python and SQL skills, including Jupyter notebooks.
- Proven knowledge of GenAI and Agentic AI technologies.
- Hands-on experience with MLOps tools like Kubeflow, Vertex AI, and GenAI/LLMops.
- Grip on, Kubernetes, Docker, and microservices architecture.
It would be nice if you also had:
- Experience with OpenAI, Llama, and Lang Chain frameworks.
- Practical experience in Pytest and Rust programming.
- Prior experience developing AI applications in the telecom domain.
- Google Cloud Professional Machine Learning Engineer certification.