AI/ML Specialist

1 day ago

Kollam, Kerala, India beBeeArtificial Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Description

As an AI/ML Engineer – 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. You must possess deep expertise in algorithm development and model deployment as production-ready products for naval applications.

The engineer will be responsible for ensuring models are modular, reusable, and deployable in resource-constrained environments. This includes fine-tuning open-source LLMs (e.g., LLaMA, Qwen, Mistral, Whisper, Wav2Vec, Conformer models) for Navy-specific tasks.

Preprocessing, labeling, and augmenting datasets are also essential responsibilities. Additionally, the engineer will implement quantization, pruning, and compression for deployment-ready AI applications.

Required Skills and Qualifications

B Tech / M.Tech in Computer Science, AI/ML, Data Science, Statistics or related field with exceptional academic record is required. Minimum 75% marks or 8.0 CGPA in relevant engineering disciplines is mandatory.

Desired specialized certifications include Professional ML certifications from Google, AWS, Microsoft, or NVIDIA, Deep Learning Specialization, Computer Vision or NLP specialization certificates, and TensorFlow/ PyTorch Professional Certification.

Benefits

The successful candidate will have the opportunity to work on end-to-end AI products, develop multiple large language models, and contribute to open-source AI projects. Experience scaling AI solutions for large user bases and optimizing models for real-time applications is highly desirable.

The ideal candidate should demonstrate practical expertise with libraries such as Hugging Face Transformers, PEFT, Fairseq, and OpenNMT. Knowledge of model compression, quantization, and deployment on GPU-enabled servers is highly desirable.

Others

The candidate should be proficient in building multilingual and domain-specific translation systems using techniques like backtranslation, domain adaptation, and knowledge distillation.

Cross-platform model deployment (cloud, edge, mobile), API design for ML model integration, and joint debugging and model-in-the-loop testing with UI and backend teams are also essential skills.

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