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Information Technology 🏢 Full Time ⭐️ Verified

Lead Machine Learning Engineer

2026 Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
2 Juli 2026
Deadline
2 Jul 2027

Job Description

Are you ready to define the future of artificial intelligence? 2026 Labs is seeking a visionary Lead Machine Learning Engineer to join our elite team in San Francisco. We are building the next generation of autonomous systems, and we need a technical architect to lead the charge.


In this role, you will bridge the gap between cutting-edge research and production-grade software. You will be responsible for designing systems that learn, adapt, and scale in real-time. If you are passionate about solving complex problems and want to work with the best minds in the industry, 2026 Labs is the place for you.

Responsibilities

  • System Architecture: Design and implement robust, scalable machine learning infrastructure using cloud-native technologies.
  • Team Leadership: Mentor a diverse team of data scientists and engineers, fostering a culture of innovation and technical excellence.
  • Research & Development: Stay ahead of the curve by researching and integrating the latest advancements in deep learning and generative AI.
  • Production Deployment: Oversee the full ML lifecycle, from data ingestion to model serving and monitoring.
  • Collaboration: Work closely with product managers and stakeholders to define technical roadmaps and deliver high-impact features.

Qualifications

  • Education: PhD in Computer Science, Mathematics, or a related quantitative field, or equivalent professional experience.
  • Experience: 5+ years of experience in machine learning engineering, with at least 2 years in a leadership or senior technical role.
  • Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
  • MLOps: Experience with CI/CD pipelines, containerization (Docker/Kubernetes), and cloud platforms (AWS/GCP/Azure).
  • Problem Solving: Proven ability to tackle complex, unstructured problems and derive actionable insights from large datasets.

Required Skills

Python PyTorch TensorFlow MLOps Machine Learning Deep Learning AWS Docker Kubernetes NLP Data Science

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