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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI/ML Engineer

Apex Innovations Inc.
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

We are at the forefront of the next industrial revolution. Apex Innovations Inc. is seeking a visionary Senior AI/ML Engineer to architect the intelligent systems of tomorrow. In 2026, we aren't just building software; we are defining the boundaries of what is possible with artificial intelligence. If you have a passion for pushing the limits of generative models, deep learning, and scalable infrastructure, this is your opportunity to lead the charge.

Join a diverse team of world-class engineers and researchers dedicated to solving humanity's most complex problems through the power of data and algorithms.

Responsibilities

  • Architect & Deploy: Design, build, and deploy state-of-the-art machine learning models and generative AI systems for production environments.
  • Optimization: Continuously improve model performance, latency, and throughput using advanced optimization techniques and distributed computing.
  • Research: Stay at the bleeding edge of AI research, implementing novel architectures and methodologies to drive innovation.
  • Collaboration: Partner with cross-functional teams including product managers, data scientists, and software engineers to translate business needs into technical solutions.
  • Mentorship: Mentor junior engineers and researchers, fostering a culture of technical excellence and continuous learning.
  • Infrastructure: Manage the end-to-end ML lifecycle, from data ingestion and processing to model serving and monitoring.

Qualifications

  • Education: Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence.
  • Programming: Expert-level proficiency in Python and frameworks such as TensorFlow, PyTorch, or JAX.
  • System Design: Strong understanding of system design principles and experience with cloud platforms (AWS, GCP, or Azure).
  • Tools: Familiarity with MLOps tools, containerization (Docker/Kubernetes), and CI/CD pipelines.
  • Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python TensorFlow PyTorch Machine Learning Deep Learning NLP Generative AI AWS Kubernetes Docker MLOps System Design

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