Artificial Intelligence (AI) Engineer

Company Description

Loyyal is a loyalty and payments innovation company that offers an Enterprise SaaS Suite powered by patented blockchain technology. We focus on disrupting the loyalty industry by delivering efficiency, security, and scalability at a low cost. Our platform is designed to reduce operational complexity and boost revenue for loyalty programs, driving customer engagement and loyalty in a competitive marketplace.

About the Role

AI Engineer

As a Senior AI Engineer, you’ll play a key role in architecting, developing, and optimizing our AI systems—from fine-tuning large language models to building robust MLOps pipelines. This is an opportunity to be part of a high-impact team shaping next-generation AI experiences.

Key Responsibilities

• Design, build, and deploy scalable AI models, with a focus on NLP, LLMs, and Generative AI use cases
• Fine-tune open-source or proprietary LLMs (e.g., LLaMA, Mistral, GPT-J) for domain-specific tasks
• Collaborate with product and engineering teams to integrate AI models into user-facing applications
• Develop MLOps pipelines using tools like MLflow, Kubeflow, or Vertex AI for model versioning, monitoring, and deployment
• Optimize inference performance, memory usage, and cost efficiency in production environments
• Apply prompt engineering, retrieval-augmented generation (RAG), and few-shot techniques where appropriate
• Conduct experiments, A/B testing, and evaluations to continuously improve model accuracy and reliability
• Stay up to date with the latest developments in AI/ML research, especially in LLM and GenAI domains
• Write clean, modular, and well-documented code and contribute to technical design reviews
• Mentor junior team members and collaborate in agile sprint cycles

Requirements

• 6+ years of experience in machine learning or AI engineering
• 2+ years working with LLMs, Transformers, or Generative AI models
• Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers)
• Experience deploying AI models in production (cloud-native or on-prem)
• Strong grasp of model fine-tuning, quantization, and serving at scale
• Familiarity with MLOps, including experiment tracking, CI/CD, and containerization (Docker, Kubernetes)
• Experience integrating AI with REST APIs, cloud services (AWS/GCP), and vector databases (e.g., Pinecone, Weaviate, FAISS)
• Understanding of ethical AI, data privacy, and fairness in model outcomes
• Strong debugging, problem-solving, and communication skills
• Experience working in agile teams with code review and version control (Git)

Nice to Have

• Hands-on experience with Retrieval-Augmented Generation (RAG) pipelines
• Familiarity with OpenAI, Anthropic, or Cohere APIs and embedding models
• Knowledge of LangChain, LlamaIndex, or Haystack for AI application orchestration
• Experience with streaming data and real-time inference systems
• Understanding of multi-modal models (e.g., combining text, image, audio inputs)
• Prior experience in a startup, product-focused, or fast-paced R&D environment

What We Offer

• Competitive compensation (base + performance-based bonuses or token equity)
• Fully remote and flexible work culture
• A front-row seat to build next-gen AI experiences in a high-growth environment
• Opportunity to shape AI strategy, tools, and infrastructure from the ground up
• Access to high-end GPU infrastructure and compute resources

How to Apply

Send your resume and a short cover letter highlighting:

• Your experience with LLMs, GenAI, and deployed AI systems
• Links to AI/ML projects, GitHub repos, or research (if public)
• Why you're interested in this role and how you envision contributing.