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Artificial Intelligence (AI) Engineer

Artificial Intelligence (AI) Engineer

LoyyalHyderabad, IN
3 days ago
Job description

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

We’re looking for a seasoned  AI Engineer  who thrives on solving complex challenges and building intelligent systems that scale. This role is ideal for someone passionate about deep learning, GenAI, and production-grade AI systems. You’ll work closely with our data, engineering, and product teams to design, build, and deploy advanced AI models across a variety of real-world use cases.

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.
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