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Senior Research Scientist - AI/ML

QuantumLeap Innovations
Cambridge
Salary Estimate
USD 140.000 – USD 180.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Join QuantumLeap Innovations at the forefront of artificial intelligence research. We're seeking a visionary Senior Research Scientist to develop cutting-edge machine learning models that will redefine industry standards. Collaborate with world-class engineers in our state-of-the-art Cambridge lab, where your breakthroughs will directly impact global tech solutions. Enjoy competitive compensation, comprehensive benefits, and unparalleled opportunities for professional growth in an environment that values intellectual curiosity and innovation.

Responsibilities

  • Design and implement novel AI/ML algorithms for complex real-world applications
  • Lead cross-functional research initiatives in natural language processing and computer vision
  • Publish findings in top-tier academic journals and industry conferences
  • Develop scalable prototypes and evaluate performance against industry benchmarks
  • Mentor junior researchers and foster collaborative innovation within the team
  • Secure external funding through grant applications and industry partnerships
  • Translate theoretical research into practical product solutions

Qualifications

  • PhD in Computer Science, Mathematics, or related quantitative field
  • 5+ years of industry experience in applied AI/ML research
  • Proven track record of peer-reviewed publications at NeurIPS/ICML/ICLR
  • Expertise in deep learning frameworks (TensorFlow/PyTorch) and distributed computing
  • Strong background in statistical modeling and experimental design
  • Demonstrated ability to lead complex research projects from concept to deployment
  • Experience with cloud platforms (AWS/GCP) and MLOps practices
  • Excellent communication skills with technical and non-technical stakeholders

Required Skills

Machine Learning Deep Learning Python Research Data Science TensorFlow PyTorch NLP Computer Vision Statistical Modeling

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