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Information Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer (Future Tech)

OmniFuture Inc.
San Francisco
Estimated Salary
USD 160.000 – USD 240.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

We are OmniFuture Inc., a pioneering technology firm dedicated to defining the infrastructure of 2026 and beyond. We are looking for a visionary Senior Machine Learning Engineer to lead the development of next-generation generative models and autonomous systems. If you want to shape the future of AI, solve complex problems at scale, and work with world-class talent, this is your opportunity.

Why Join Us?

  • Future-Ready Technology: Work on cutting-edge AI architectures designed for the demands of 2026.
  • Competitive Compensation: Salary up to $240,000 plus equity and performance bonuses.
  • Remote-First Culture: Flexible working arrangements with a focus on output over hours.

Key Responsibilities:

  • Architect and deploy scalable machine learning pipelines for generative AI and predictive analytics.
  • Collaborate with cross-functional teams (Data Science, Product, and Engineering) to translate business needs into technical solutions.
  • Optimize model inference speed and reduce computational costs by 30%.
  • Lead code reviews and establish best practices for MLOps and model governance.
  • Research emerging trends in artificial intelligence to keep our technology stack ahead of the curve.
  • Mentor junior engineers and contribute to the technical roadmap.

Qualifications:

  • 5+ years of experience in Machine Learning Engineering, with a focus on Deep Learning or NLP.
  • Proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
  • Strong understanding of MLOps, CI/CD, and data engineering pipelines.
  • Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
  • Master’s degree in Computer Science, AI, or a related field is preferred.

Responsibilities

  • Architect and deploy scalable machine learning pipelines for generative AI and predictive analytics.
  • Collaborate with cross-functional teams (Data Science, Product, and Engineering) to translate business needs into technical solutions.
  • Optimize model inference speed and reduce computational costs by 30%.
  • Lead code reviews and establish best practices for MLOps and model governance.
  • Research emerging trends in artificial intelligence to keep our technology stack ahead of the curve.
  • Mentor junior engineers and contribute to the technical roadmap.

Qualifications

  • 5+ years of experience in Machine Learning Engineering, with a focus on Deep Learning or NLP.
  • Proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
  • Strong understanding of MLOps, CI/CD, and data engineering pipelines.
  • Excellent communication skills and the ability to explain complex technical concepts to non-technical stakeholders.
  • Master’s degree in Computer Science, AI, or a related field is preferred.

Required Skills

Python Machine Learning Deep Learning NLP PyTorch TensorFlow AWS GCP Docker Kubernetes MLOps AI Architecture

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