Machine Learning/Deep Learning Engineer

Position Overview:

• We are seeking a highly skilled and motivated

  Machine Learning/Deep Learning Engineer

  with expertise in neural network development, GenAI technologies, and cloud-native deployment on AWS.
• This role will be instrumental in designing, training, and deploying advanced AI models across text, image, and audio domains, while also managing scalable cloud infrastructure and APIs.
  

Key Responsibilities

• Design and implement deep learning models using

  TensorFlow, PyTorch, and transformer architectures.

• Fine-tune pre-trained models for domain-specific tasks involving text, image, or audio datasets.
• Optimize and deploy models on

  NVIDIA GPU hardware (e.g., A100, H100) for high-performance inference.

• Develop

  LLMOps

  context aware pipelines for

  chat applications

  using python frameworks.
• Collaborate with data scientists and product teams to integrate models into production systems.
  

API Development & Integration

• Develop and maintain RESTful and

  gRPC APIs

  for model serving and data access.
• Manage the

  full API lifecycle,

  including versioning, documentation, and security.
• Integrate APIs with internal and external applications using FastAPI or similar Python frameworks.
  

AWS Cloud Engineering

• Create and manage AWS Container Apps, Container Registries, and Docker images.
  
• Deploy and monitor AWS Web Apps for hosting AI services and dashboards.
  
• Automate CI/CD pipelines using GitHub Actions for seamless deployment and updates.
  

Required Qualifications

• 2+ years

  of experience in Python development with a focus on deep learning.
• Hands-on experience with transformers, Hugging Face, and custom model training.
  
• Proven track record of deploying models on GPU-based infrastructure.
  

• Strong understanding of API design principles and microservices architecture.

• Experience with

  AWS cloud services, Docker, and GitHub Actions.

• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
  

Preferred Qualifications

• Experience with multi-modal models or generative AI applications.
  
• Familiarity with MLOps tools and practices.
  
• Contributions to open-source AI projects or publications in relevant fields.
• Mathematics/Physics background preferred