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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI/ML Engineer

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Are you ready to define the technological landscape of 2026? Nexus Future Labs is looking for a visionary Senior AI/ML Engineer to lead our cutting-edge research division. In this pivotal role, you will architect scalable machine learning systems that will power our next-generation products.

We are not just building software; we are building the future. Our team focuses on Generative AI, Large Language Models, and autonomous agents designed to revolutionize enterprise efficiency. If you have a passion for pushing the boundaries of what is possible in Artificial Intelligence and want to work in a high-performance, remote-first environment, we want to meet you.

Responsibilities

  • Architect & Deploy: Design, train, and deploy state-of-the-art machine learning models and large language models (LLMs) with a focus on latency and throughput optimization.
  • R&D Leadership: Spearhead research initiatives to explore emerging AI paradigms, ensuring our technology stack remains ahead of the 2026 market curve.
  • System Optimization: Optimize existing inference pipelines to reduce operational costs and improve model performance in production environments.
  • Collaboration: Work closely with cross-functional teams of product managers, data scientists, and software engineers to translate business requirements into technical solutions.
  • Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.

Qualifications

  • Education: M.S. or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
  • Experience: 5+ years of professional experience in machine learning engineering, preferably in a high-growth startup or tech giant.
  • Core Skills: Proficiency in Python, PyTorch, TensorFlow, and SQL.
  • AI Expertise: Deep understanding of Deep Learning architectures, Natural Language Processing (NLP), and Reinforcement Learning.
  • Problem Solving: Strong analytical skills with the ability to debug complex distributed systems and model training failures.
  • Communication: Excellent verbal and written communication skills for technical documentation and stakeholder presentations.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning NLP SQL AWS Docker Kubernetes

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