Lead ML / Data Scientist

You will be responsible for leading the architecture and development of transformer-based AI systems. This includes driving the technical direction for NLP, LLM, and multilingual AI initiatives. Your role will involve mentoring and guiding junior ML engineers and researchers, optimizing model performance using techniques such as LoRA, QLoRA, PEFT, quantization, and distributed training, as well as collaborating with platform teams for GPU infrastructure and scalable deployments. Key Responsibilities: - Lead the architecture and development of transformer-based AI systems - Drive technical direction for NLP, LLM, and multilingual AI initiatives - Mentor and guide junior ML engineers and researchers - Optimize model performance using LoRA, QLoRA, PEFT, quantization, and distributed training techniques - Collaborate with platform teams for GPU infrastructure and scalable deployments Qualifications Required: - 6+ years of experience in Data Science / Machine Learning / NLP - Proven experience in model training and fine-tuning using custom datasets - Hands-on experience with Hugging Face, PyTorch, or TensorFlow - Knowledge of Vector Databases like Pinecone, Milvus for embeddings and semantic search in translation or LLM applications - Experience with distributed training, GPU optimization, and NLP evaluation metrics - Familiarity with LoRA, QLoRA, PEFT, RLHF, SFT, Machine Translation systems - Research/publication background in AI/ML/NLP - Experience with OpenAI/GPT API integrations without model training - Proficiency in Python, AWS/GPU Infrastructure, Docker/Kubernetes, Vector Databases, and NLP Tooling You should also possess the ability to bridge research and production AI systems effectively. You will be responsible for leading the architecture and development of transformer-based AI systems. This includes driving the technical direction for NLP, LLM, and multilingual AI initiatives. Your role will involve mentoring and guiding junior ML engineers and researchers, optimizing model performance using techniques such as LoRA, QLoRA, PEFT, quantization, and distributed training, as well as collaborating with platform teams for GPU infrastructure and scalable deployments. Key Responsibilities: - Lead the architecture and development of transformer-based AI systems - Drive technical direction for NLP, LLM, and multilingual AI initiatives - Mentor and guide junior ML engineers and researchers - Optimize model performance using LoRA, QLoRA, PEFT, quantization, and distributed training techniques - Collaborate with platform teams for GPU infrastructure and scalable deployments Qualifications Required: - 6+ years of experience in Data Science / Machine Learning / NLP - Proven experience in model training and fine-tuning using custom datasets - Hands-on experience with Hugging Face, PyTorch, or TensorFlow - Knowledge of Vector Databases like Pinecone, Milvus for embeddings and semantic search in translation or LLM applications - Experience with distributed training, GPU optimization, and NLP evaluation metrics - Familiarity with LoRA, QLoRA, PEFT, RLHF, SFT, Machine Translation systems - Research/publication background in AI/ML/NLP - Experience with OpenAI/GPT API integrations without model training - Proficiency in Python, AWS/GPU Infrastructure, Docker/Kubernetes, Vector Databases, and NLP Tooling You should also possess the ability to bridge research and production AI systems effectively.