Transformer ML Engineer — From Research to Production
Skale
New York (NY)
On-site
USD 120,000 - 160,000
Full time
14 days+
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Job summary
Skale is seeking a Machine Learning Engineer in New York to design, fine-tune, and evaluate large-scale transformer models. The role involves leading end-to-end ML pipelines and collaborating with product teams to deliver real-world solutions. Candidates should have 3+ years of hands-on experience with transformer models, strong Python proficiency, and deep familiarity with the Hugging Face ecosystem. This position offers a chance to impact the next generation of intelligent systems.
Qualifications
3+ years of hands-on experience with transformer-based models in NLP, CV, or multi-modal settings.
Strong proficiency in Python; deep familiarity with PyTorch and the Hugging Face ecosystem.
Solid understanding of attention mechanisms, positional encodings, and training dynamics.
Responsibilities
Design, fine-tune, and evaluate large-scale transformer architectures (BERT, GPT, T5, and beyond).
Lead end-to-end ML pipelines: data curation, training, optimisation, and serving.
Apply techniques such as LoRA, RLHF, and quantisation to improve model efficiency and alignment.
Collaborate with product and infrastructure teams to ship models that solve real-world problems.
Stay current with research; translate papers into practical, production-ready implementations.
Skills
Transformer-based models
Python proficiency
PyTorch
Attention mechanisms
Model deployment
Tools
Hugging Face
ONNX
TorchServe
Job description
Skale is seeking a Machine Learning Engineer in New York to design, fine-tune, and evaluate large-scale transformer models. The role involves leading end-to-end ML pipelines and collaborating with product teams to deliver real-world solutions. Candidates should have 3+ years of hands-on experience with transformer models, strong Python proficiency, and deep familiarity with the Hugging Face ecosystem. This position offers a chance to impact the next generation of intelligent systems.