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Information Technology 🏢 Full Time ⭐️ Verified

AI/ML Engineer - 2026 Readiness

Apex Innovations
San Francisco
Estimated Salary
USD 160.000 – USD 230.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Apex Innovations is at the forefront of defining the technological landscape for the year 2026. We are seeking a visionary AI/ML Engineer to join our elite technical team. In this role, you will architect the next generation of machine learning systems, ensuring our solutions are not only state-of-the-art today but are scalable and future-proof for the challenges of tomorrow.

Why join us?
We are a remote-first company with a strong presence in the Bay Area, offering competitive compensation, comprehensive benefits, and the opportunity to shape the future of AI.

Responsibilities

  • Design, train, and deploy advanced machine learning models, focusing on scalability and accuracy for 2026 standards.
  • Optimize and fine-tune large language models (LLMs) and generative AI architectures.
  • Build and maintain robust data pipelines to support high-throughput training and inference.
  • Collaborate with cross-functional teams to integrate AI solutions into product workflows.
  • Research cutting-edge algorithms and contribute to open-source projects to drive industry innovation.
  • Ensure ethical AI practices, data privacy, and model interpretability in all deliverables.

Qualifications

  • 5+ years of professional experience in software engineering and machine learning.
  • Strong proficiency in Python, PyTorch, TensorFlow, or Scikit-learn.
  • Deep understanding of NLP, Computer Vision, or Reinforcement Learning.
  • Experience with MLOps, containerization (Docker/Kubernetes), and cloud platforms (AWS/GCP/Azure).
  • Excellent problem-solving skills and the ability to translate business requirements into technical solutions.
  • Master's degree or PhD in Computer Science, Mathematics, or a related field is preferred.

Required Skills

Python Machine Learning Deep Learning NLP PyTorch TensorFlow AWS GCP MLOps Docker Kubernetes SQL Data Pipelines

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