Machine Learning Engineer
Core
Designing, developing, and optimizing transformer-based NLP models and Large Language Models (LLMs) for multilingual translation and custom architectures.
Role type
Machine Learning Engineer (NLP/Transformers)
Builds
Production-grade AI systems, multilingual translation models, and scalable NLP solutions
Domain
Natural Language Processing (NLP), Transformer-based AI
Deliverable
production ML models
Required skills
Transformer architectures, LLMs, Seq2Seq models, attention mechanisms, Python, PyTorch, TensorFlow, Hugging Face Transformers, vector databases, GPU acceleration, distributed training, model optimization (LoRA, QLoRA, PEFT, quantization), tokenization (BPE, SentencePiece), model evaluation metrics (BLEU, perplexity)
Preferred skills
null
Technologies
PyTorch, TensorFlow, Hugging Face Transformers, Pinecone, Milvus
Responsibilities
Design and optimize transformer-based AI/ML models for NLP; Build and maintain end-to-end machine learning pipelines; Train and fine-tune transformer models on large-scale custom datasets; Work with Seq2Seq, encoder-decoder architectures, and modern LLM architectures; Optimize models using techniques such as LoRA, QLoRA, PEFT, quantization, and distributed training; Develop tokenization pipelines using BPE and SentencePiece; Evaluate model performance using BLEU, perplexity, and custom benchmarks; Collaborate with infrastructure teams to manage GPU environments and scalable AI deployments; Implement efficient model serving and inference optimization.
Seniority
Mid-level, hands-on IC