Main Responsibilities:
- Design, develop, and deploy (Artificial Intelligence) AI and Generative AI models, including data preparation, feature engineering, training, evaluation, versioning, and monitoring.
- Establish and implement robust Machine Learning Operations (MLOps) architecture to automate model lifecycle processes, ensuring quality, reliability, and scalability.
- Develop REST APIs, Python-based applications, and maintain embeddings while industrializing internal Proof of Concepts (POCs).
- Work closely with business teams to translate their needs into actionable scientific questions and present analyses and recommendations clearly.
- Partner with the Cloud Centre of Excellence and infrastructure teams to ensure seamless project execution.
- Provide comprehensive documentation and handover processes to ensure smooth operational transitions.
Qualifications and Profile:
- Degree in Computer Science or any related discipline.
- At least 2-7 years in developing AI/ML technology solutions, with expertise in machine learning, deep learning, generative AI, and MLOps.
- Proficiency in AI frameworks such as TensorFlow, PyTorch, and Scikit.
- Knowledge of Generative AI and LLM technologies using Retrieval-Augmented Generation (RAG) patterns on public cloud platforms.
- Excellent programming skills in Python, .NET, or Java.
- Expertise in DevOps/MLOps/LLMOps tools like GitLab CI/CD, Kubernetes, AWS Cloud, AWS Bedrock, and AWS Sagemaker.
- Skilled in cleaning, preprocessing, and transforming datasets for model training.
- Awareness of ethical principles in Generative AI and embeddings.
- Effective communication and collaborative team skills.
- Curiosity and eagerness to learn and innovate.
Travel: Occasional
Interested candidates may send in their resume and cover letter directly to [email protected] (R1434374), stating the position as the subject title in the email.
Jireli Gem Mejia Cabria EA License No.: 02C3423 Personnel Registration No.: R1434374
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