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Information Technology 🏒 Full Time ⭐️ Verified

Lead Machine Learning Engineer

2026
San Francisco
Estimated Salary
USD 160.000 – USD 220.000
Live Update
18 Mei 2026
Deadline
18 Mei 2027

Job Description

We are seeking a visionary Lead Machine Learning Engineer to join our elite team at 2026. As we stand on the precipice of the next industrial revolution, your work will define the trajectory of our core products. You will be responsible for architecting the neural networks that power our autonomous systems and predictive analytics engines.

In this role, you will not just write code; you will shape the future of technology. You will collaborate with a diverse group of engineers, data scientists, and product designers to bring cutting-edge AI solutions to life. If you are passionate about the future and eager to solve the world's most complex problems, we want to hear from you.

Responsibilities

  • Architect Scalable ML Systems: Design and deploy robust, large-scale machine learning models and inference pipelines using Python, PyTorch, and TensorFlow.
  • Model Optimization: Continuously optimize model performance, accuracy, and latency to ensure real-time processing capabilities.
  • Research & Innovation: Stay at the forefront of AI research, evaluating and implementing new techniques such as Generative Adversarial Networks (GANs) and Transformer architectures.
  • Collaboration: Partner with cross-functional teams to translate business requirements into technical specifications and engineering solutions.
  • Code Review & Mentorship: Lead code reviews, conduct technical architecture discussions, and mentor junior engineers to foster a culture of excellence.

Qualifications

  • Education: Master’s or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related field.
  • Experience: 5+ years of professional experience in machine learning engineering, with a proven track record of deploying production-grade models.
  • Technical Skills: Proficiency in Python, C++, and SQL; deep understanding of deep learning frameworks (TensorFlow, PyTorch, Keras).
  • Cloud Expertise: Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Problem Solving: Exceptional analytical and problem-solving skills with a focus on optimizing system architecture.

Required Skills

Python Machine Learning Deep Learning TensorFlow PyTorch AWS Kubernetes Docker SQL C++

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