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Information Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer

Nexus BioTech Solutions
San Francisco
Salary Estimate
USD 180.000 – USD 250.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Nexus BioTech Solutions is revolutionizing the intersection of biology and artificial intelligence. We are seeking a visionary Senior Machine Learning Engineer to lead our research division in developing scalable algorithms that push the boundaries of what is possible in genomics and drug discovery. If you are passionate about solving complex problems with cutting-edge technology and want to make a tangible impact on human health, we want to meet you.

As a key member of our R&D team, you will be responsible for architecting and deploying deep learning models that process vast datasets to uncover hidden patterns in biological data. You will work closely with data scientists, bioinformaticians, and software engineers to ensure our solutions are not only accurate but also scalable and production-ready.

Responsibilities

  • Design, develop, and optimize state-of-the-art machine learning and deep learning models.
  • Collaborate with cross-functional teams to integrate AI solutions into existing bioinformatics pipelines.
  • Perform exploratory data analysis (EDA) and feature engineering on large-scale genomic datasets.
  • Implement MLOps best practices to ensure model monitoring, versioning, and deployment.
  • Conduct rigorous validation and testing to ensure model accuracy and robustness.
  • Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.

Qualifications

  • Master’s or PhD degree in Computer Science, Statistics, Bioinformatics, or a related quantitative field.
  • Minimum of 5 years of professional experience in machine learning, deep learning, or data science.
  • Strong proficiency in Python, PyTorch, TensorFlow, or Scikit-learn.
  • Extensive experience with Natural Language Processing (NLP) or Computer Vision (CV) is highly desirable.
  • Proven track record of deploying models to production environments using cloud infrastructure (AWS, GCP, or Azure).
  • Excellent problem-solving skills and ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning Deep Learning NLP Computer Vision TensorFlow PyTorch AWS GCP MLOps Genomics Data Science Scikit-learn

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