Machine Learning Engineer

March 19

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Neural Magic

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GPU-class AI performance on commodity CPUs. #SoftwareDeliveredAI

machine learning • deep learning • artificial intelligence

11 - 50

Description

• Use your understanding of machine learning to tackle meaningful technical problems • Collaborate with research and product development teams to build machine learning products • Prototype and implement appropriate ML algorithms, tools, and pipelines • Create and manage training and deployment pipelines • Collaborate with a cross-functional team about market requirements and best practices • Keep abreast of developments in the field

Requirements

• Proven experience as a machine learning engineer or similar role • Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc • Knowledge of common ML frameworks (like PyTorch or Keras) and libraries (like NumPy and scikit-learn) • Strong programming skills with proven experience implementing Python-based machine learning solutions • Experience with engineering and supporting ML pipelines in a popular ML framework such as PyTorch, TensorFlow, jax, etc. • Experience with engineering and maintaining training and/or deployment pipelines for Generative models / NLG / LLMs • Ability to interpret and implement research ideas and algorithms • Creative, collaborative, and innovation-focused • Strong sense of project ownership and personal responsibility • Bachelor's in Computer Science, Mathematics or similar field

Benefits

• Health Care Plan (Medical, Dental & Vision) • Retirement Plan (401k, IRA) • Paid Time Off (Vacation, Sick & Public Holidays) • Family Leave (Maternity, Paternity) • Short Term & Long Term Disability • Training & Development • Work From Home • Free Food & Snacks • Wellness Resources • Stock Option Plan