AI Engineer

GeoIQ

Required skills

Website: geoiq.ai
Job details:
Responsibilities

Design and implement AI-driven solutions across domains such as LLMs, Generative AI, NLP, and Computer Vision.
Research, prototype, and evaluate state-of-the-art AI models and architectures for real-world applications.
Build retrieval-augmented generation (RAG) pipelines and integrate AI models into customer-facing products.
Work with engineers and product teams to embed AI capabilities into platforms and workflows.
Optimise AI models for accuracy, scalability, and production efficiency.
Stay up-to-date with advancements in Generative AI, foundation models, and applied AI frameworks.

Requirements

Bachelor's/Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
1-2 years of experience in building and deploying AI applications.
Strong proficiency in Python and AI/ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, and Scikit-learn.
Hands-on experience with LLMs, embeddings, prompt engineering, or fine-tuning foundation models.
Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus.
Understanding of vector databases (Pinecone, Qdrant, Weaviate, FAISS) is desirable.
Strong problem-solving skills with the ability to translate business needs into applied AI solutions.
Excellent communication and cross-team collaboration skills.
Experience with Generative AI (LLMs, diffusion models, multimodal AI).
Familiarity with RAG, orchestration frameworks (LangChain, LlamaIndex, Haystack).
Exposure to MLOps/AIOps practices and CI/CD pipelines for AI workflows.
Contributions to AI/ML open-source projects.

This job was posted by Jancy Alice Challam from GeoIQ. Click on Apply to know more.

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