Software Engineer

7 days ago

Noida, Uttar Pradesh, India GoodSpace AI Full time US$ 90,000 - US$ 1,20,000 per year

Warning
: This is a startup role. We're looking for risk-takers who want to build something extraordinary from the ground up. If you want stability and predictability, this isn't for you.

We are seeking an AI/ML Engineer who specializes in fine-tuning and deploying large language models and voice models. The ideal candidate will have hands-on experience with modern AI frameworks and a proven track record of building production-ready AI solutions.

Model Development & Fine-tuning

  • Fine-tune chat completion models (LLaMA, GPT variants, etc.) for domain-specific applications
  • Develop and optimize resume parsing systems using NLP techniques
  • Build and maintain vector embedding pipelines for semantic search and retrieval systems
  • Deploy and optimize voice models (Ultravox, Whisper, etc.) for production use
  • Create custom training datasets and implement data augmentation strategies

We will work on

  • Languages
    : Python (expert level), familiarity with JavaScript/TypeScript is a plus
  • Frameworks
    : PyTorch, Transformers, Langchain, LlamaIndex
  • LLM Tools
    : PEFT, LoRA, QLoRA, vLLM, Ollama
  • Vector DBs
    : Experience with at least one (Pinecone, Weaviate, ChromaDB, Qdrant)
  • Voice/Audio
    : Experience with Ultravox, Whisper, or similar voice models
  • Cloud
    : AWS/GCP/Azure ML services
  • MLOps
    : Weights & Biases, MLflow, model versioning
  • APIs
    : FastAPI, REST APIs, WebSockets for real-time inference

What You'll Work On

  • Building intelligent resume parsing systems with high accuracy
  • Creating conversational AI agents for recruitment workflows
  • Implementing semantic search across large document corpuses
  • Deploying voice-based AI assistants for candidate interactions
  • Fine-tuning models for specific HR and recruitment use cases

How to Apply

Please share:

  1. Your resume highlighting relevant ML/AI projects
  2. GitHub/Portfolio links showcasing your work
  3. Brief description of your most challenging model fine-tuning project
  4. Any deployed models or APIs you've built (with links if publicly accessible)

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