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Information Technology 🏢 Full Time ⭐️ Verified

Lead AI/ML Engineer - San Francisco, CA

Apex Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

Shape the Intelligent Future of 2026

Apex Innovations is seeking a visionary Lead AI/ML Engineer to architect the systems that will define the next decade of technology. As we prepare for the rapid evolution of the AI landscape in 2026, you will be responsible for building scalable, high-performance infrastructure that powers our global AI solutions. This is a unique opportunity to lead a world-class team and deploy cutting-edge machine learning models at enterprise scale.

In this role, you will bridge the gap between theoretical research and production-grade engineering. You will drive the technical vision, optimize our deep learning pipelines, and ensure our AI systems are resilient, ethical, and ready for the future.

Responsibilities

  • Architect Advanced ML Pipelines: Design and maintain robust, end-to-end infrastructure for training and deploying large-scale neural networks and deep learning models.
  • Lead Technical Strategy: Define the technical roadmap for AI infrastructure, ensuring alignment with business goals and the 2026 technological horizon.
  • Optimize Performance: Implement advanced techniques (e.g., model quantization, distributed training) to maximize computational efficiency and reduce latency.
  • Cloud & DevOps Integration: Leverage AWS, Azure, or GCP to build serverless, scalable architectures that handle massive data throughput.
  • Team Leadership: Mentor a diverse team of data scientists and engineers, fostering a culture of innovation, code quality, and continuous learning.
  • Collaboration: Work closely with product managers and researchers to translate complex requirements into scalable technical solutions.

Qualifications

  • Experience: 7+ years of software engineering experience with at least 4 years specifically in Machine Learning or Data Engineering.
  • Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
  • Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and SQL. Experience with Kubernetes and Docker is essential.
  • Cloud Expertise: Deep understanding of cloud-native services and container orchestration.
  • Strategic Vision: Demonstrated ability to anticipate future trends and build flexible systems that adapt to the evolving tech landscape.
  • Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Kubernetes Docker AWS Azure Machine Learning Deep Learning Distributed Systems Data Engineering

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