Advanced AI/ML Expert Wanted

9 hours ago

Bhavnagar, Gujarat, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,25,00,000

Job Opportunity: AI/ML Expert

We are seeking an exceptional AI/ML Engineer to join our team. As a core algorithm and model expert, you will be responsible for designing, developing, and optimizing advanced AI/ML models for computer vision, generative AI, audio processing, predictive analysis, and NLP applications.

Key Responsibilities:
  • Design and train models using naval-specific data and deliver them in the form of end products.
  • Fine-tune open-source LLMs (e.g. LLaMA, Qwen, Mistral, Whisper, Wav2Vec, Conformer models) for Navy-specific tasks.
  • Preprocess, label, and augment datasets.
  • Implement quantization, pruning, and compression for deployment-ready AI applications.
  • The engineer will be responsible for the development, training, fine-tuning, and optimization of Large Language Models (LLMs) and translation models for mission-critical AI applications of the Indian Navy.
Required Skills and Qualifications:
  • B Tech/M.Tech in Computer Science, AI/ML, Data Science, Statistics, or related field with exceptional academic record.
  • Minimum 75% marks or 8.0 CGPA in relevant engineering disciplines.
  • Professional ML certifications from Google, AWS, Microsoft, or NVIDIA.
  • Deep Learning Specialization.
  • Computer Vision or NLP specialization certificates.
  • TensorFlow/PyTorch Professional Certification.
Benefits:
  • Hands-on experience with at least 2 major AI domains.
  • Experience deploying models in production environments.
  • Contribution to open-source AI projects.
  • Led development of multiple end-to-end AI products.
  • Experience scaling AI solutions for large user bases.
  • Track record of optimizing models for real-time applications.
Others:
  • End-to-end ML pipeline development (data ingestion to model serving).
  • User feedback integration for model improvement.
  • Cross-platform model deployment (cloud, edge, mobile).
Responsibilities:
  • Maintain reproducible pipelines (e.g., with MLFlow, DVC, Weights & Biases).
  • Collaborate with Backend Engineer for integration via standard formats (ONNX, TorchScript).
  • Generate reusable inference modules that can be plugged into microservices or edge devices.

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