ML Engineer

About the Role

Responsibilities

• Own the training and fine-tuning of ML models (NLP, speech, vision, multimodal).
• Prepare and manage datasets at scale, with augmentation pipelines.
• Optimize models (quantization, pruning, distillation) for low-latency use cases.
• Work with Hugging Face, LangChain/LangGraph, and custom pipelines.
• Integrate models into APIs/services with the full-stack team.
• Contribute to generative AI features (avatars, voice, immersive video).
• Research and recommend frameworks/tools for faster iteration.
  

Key Skills & Experience

• 2-4 years professional AI/ML experience
• Strong Python, PyTorch/TensorFlow
• Hands-on Hugging Face (Transformers, Diffusers)
• Understanding of agentic frameworks (LangChain, LangGraph)
• Model evaluation and benchmarking experience
• Basic experience with vector DBs (pgvector, Pinecone, OpenSearch)
• Familiarity with cloud ML services (AWS Bedrock/SageMaker, Vertex, or Azure AI)

Nice to Have

• Experience with speech and generative media (Whisper, ElevenLabs, Stable Diffusion).
• Docker, GitLab CI/CD, Linux server workflows.
• Contribution to research papers, open-source repos, or Kaggle competitions.