
AI/ML Software Engineer
1 day ago
We are seeking a highly skilled AI/ML software engineer to join our team. The ideal candidate will have expertise in designing, developing, and optimizing advanced AI/ML models for computer vision, generative AI, audio processing, predictive analysis, and NLP applications.
The successful candidate will be responsible for designing and training AI/ML models using naval-specific data and delivering them as end products. They will also fine-tune open-source LLMs for Navy-specific tasks, preprocess, label, and augment datasets, implement quantization, pruning, and compression for deployment-ready AI applications, and develop reusable inference modules that can be plugged into microservices or edge devices.
The ideal candidate will possess a strong foundation in transformer-based architectures, hands-on experience with pretraining and fine-tuning methodologies, proficiency in building multilingual and domain-specific translation systems, and practical expertise with libraries such as Hugging Face Transformers, PEFT, Fairseq, and OpenNMT.
They will also collaborate with backend engineers for integration via standard formats, maintain reproducible pipelines, and generate reusable inference modules.
Key qualifications include a B Tech/M.Tech in Computer Science, AI/ML, Data Science, Statistics, or related field, exceptional academic record, professional ML certifications from Google, AWS, Microsoft, or NVIDIA, and deep learning specialization certificates.
Core skills and tools required include languages Python, C++, Rust, frameworks PyTorch, TensorFlow, Hugging Face Transformers, optimized inference ONNX Runtime, TensorRT, TorchScript, data tooling Pandas, NumPy, Scikit-learn, OpenCV, security awareness data sanitization, adversarial robustness, model watermarking, and core AI/ML competencies deep learning architectures, computer vision, natural language processing, and generative AI.
Experience requirements include hands-on experience with at least two 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, and experience mentoring technical teams.
Product development skills required include end-to-end ML pipeline development, user feedback integration for model improvement, cross-platform model deployment, API design for ML model integration, defining model interfaces, building CLI and REST-compatible inference tools, maintaining shared code libraries, and joint debugging and model-in-the-loop testing with UI and backend teams.
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