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Description
We are seeking a Machine Learning Scientist with a strong track record in applied AI research. You will train and improve the models behind large-scale search, retrieval, and ranking systems, and turn the latest research into production-ready models.
Minimum Qualifications
PhD in Computer Science, Machine Learning, or a related field, or MS with 5+ years of applied ML research experienceStrong deep learning and NLP fundamentals, with hands-on experience training and fine-tuning transformer modelsProficiency in PyTorch and strong Python programming skillsExperience with post-training, fine-tuning, or representation learning for large modelsExperience designing rigorous experiments and evaluations, and analyzing model behaviorDemonstrated ability to turn research ideas into working systems
Preferred Qualifications
* Experience training embedding, retrieval, or reranking models (e.g., contrastive learning, late-interaction / ColBERT-style models, cross-encoders)* Experience with parameter-efficient fine-tuning (LoRA, QLoRA, PEFT) and preference optimization (RLHF, DPO)* Experience with distributed training (e.g., FSDP, DeepSpeed) and multi-GPU workloadsExperience with inference engines and serving frameworks (vLLM, SGLang, Triton)Experience with model efficiency: quantization, pruning, distillation, or analysis of model internalsExperience with data-centric ML, such as data curation, data attribution, or training-data robustnessFamiliarity with cloud environments (AWS or GCP) and containerization (Docker, Kubernetes)Publications at top venues (e.g., NeurIPS, ICLR, ICML, CVPR, ACL), and service as a reviewer or program committee member
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