Applied AI/ML Engineer

3 weeks ago

Bengaluru, India Recro Full time

Who You AreYou're an ML Research Engineer with 2+ years of experience who bridges the gap betweencutting-edge research and production systems. You're passionate about training models thatperform exceptionally well not just on benchmarks but in real-world applications. You enjoydiving deep into model architectures, experimenting with training techniques, and buildingrobust evaluation frameworks that ensure model reliability in critical applications.Responsibilities● Train and fine-tune models for speech recognition (ASR) or NLP tasks including intentclassification, Named Entity Recognition (NER), and entity linking to knowledge bases inmultilingual healthcare contexts● Build data pipelines for dataset collection, annotation, augmentation, and synthetic datageneration to address multilingual and low-resource challenges● Design and implement comprehensive evaluation frameworks to measure modelperformance across precision, recall, F1, and domain-specific benchmarks● Research and implement state-of-the-art techniques from academic papers to improvemodel performance on ASR, NER, intent classification, or entity linking tasks● Optimize models through fine-tuning techniques (LoRA, QLoRA, full fine-tuning) andarchitecture experiments for production deployment● Collaborate with AI engineers to deploy optimized models into production systems andensure reliability in critical healthcare applicationsQualificationsRequired● 2+ years of experience in ML/DL with focus on training and fine-tuning productionmodels● Deep expertise in speech recognition systems (ASR) or natural language processing(NLP), including transformer architectures● Strong understanding of NER, intent classification, or entity linking systems withhands-on experience building these components● Proven experience with model training frameworks (PyTorch, TensorFlow) anddistributed training● Strong understanding of evaluation metrics and ability to design domain-specificbenchmarks● Experience with modern speech models (Whisper, Wav2Vec2, Conformer) or NLPmodels for NER/intent classification (BERT, RoBERTa, BiLSTM-CRF)● Experience with LLM fine-tuning techniques (LoRA, QLoRA, full fine-tuning) orknowledge base integration methods● Proficiency in handling multilingual datasets and cross-lingual transfer learning● Track record of improving model performance through data engineering andaugmentation strategiesNice to Have● Published research or significant contributions to open-source ML projects● Experience with entity linking to knowledge bases (Wikipedia, DBpedia, domain-specificontologies)● Experience with model optimization techniques (quantization, distillation, pruning)● Background in low-resource language modeling or few-shot learning approaches● Experience building evaluation frameworks for production ML systems● Understanding of information extraction pipelines and knowledge graph construction

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