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Senior AI & Machine Learning Engineer (2026 Vision)

FutureTech Innovations
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
23 Mei 2026
Deadline
23 Mei 2027

Job Description

Are you ready to architect the future of artificial intelligence? FutureTech Innovations is looking for a visionary Senior AI & Machine Learning Engineer to lead our cutting-edge research division. As we prepare for the technological leap into 2026, we need a thought leader who can bridge the gap between theoretical AI and real-world application.

In this role, you will be at the forefront of developing Generative AI models, optimizing neural architectures, and ensuring ethical AI deployment across our global platform. Join a team of elite engineers and data scientists dedicated to pushing the boundaries of what is possible.

Responsibilities

  • Lead the design and implementation of next-generation Large Language Models (LLMs) and generative AI frameworks.
  • Optimize model inference latency and reduce computational costs for high-scale production environments.
  • Collaborate with cross-functional teams to integrate AI capabilities into consumer-facing products.
  • Establish best practices for data privacy, security, and ethical AI governance.
  • Conduct research on novel neural network architectures and algorithms.
  • Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.

Qualifications

  • Master’s or PhD in Computer Science, Mathematics, or a related field.
  • 5+ years of professional experience in AI/ML, with a focus on Deep Learning and NLP.
  • Strong proficiency in Python, PyTorch, TensorFlow, and Hugging Face.
  • Proven track record of deploying scalable ML models in production.
  • Experience with MLOps, cloud infrastructure (AWS/GCP), and containerization (Docker/Kubernetes).
  • Excellent problem-solving skills and ability to work in a fast-paced, agile environment.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP LLMs Generative AI MLOps Docker Kubernetes AWS GCP AI Ethics

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