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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI/ML Engineer

Apex Logic
San Francisco
Estimated Salary
USD 160.000 – USD 210.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Are you ready to engineer the future of intelligent systems? Apex Logic is seeking a visionary Senior AI/ML Engineer to join our elite team in San Francisco. We are not just building software; we are architecting the next generation of automated intelligence that will redefine industry standards.

In this pivotal role, you will leverage state-of-the-art deep learning frameworks to solve complex problems and drive scalable solutions. If you thrive in a fast-paced, high-performance environment and want to make a tangible impact on the world, we want to hear from you.

Responsibilities

  • Design, train, and deploy scalable machine learning models and neural networks.
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical requirements.
  • Perform rigorous data analysis, feature engineering, and model optimization to improve accuracy and performance.
  • Implement best practices for MLOps, ensuring models are reproducible and robust in production environments.
  • Conduct A/B testing and performance analysis to iterate on features and enhance user experience.
  • Mentor junior engineers and conduct code reviews to foster a culture of technical excellence.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
  • 5+ years of professional experience in machine learning, deep learning, or artificial intelligence.
  • Strong proficiency in Python, PyTorch, TensorFlow, or Scikit-learn.
  • Deep understanding of NLP, Computer Vision, or Reinforcement Learning.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
  • Excellent problem-solving skills and the ability to work independently in a remote-first culture.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP AWS Docker Kubernetes

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