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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI/ML Engineer (2025 Focus)

Nexus Future Labs
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
Live Update
16 Mei 2026
Deadline
16 Mei 2027

Job Description

We are building the intelligence layer for the next generation of enterprise software. Nexus Future Labs is seeking a visionary Senior AI/ML Engineer to spearhead our advanced model development initiatives. You will be at the forefront of applying Large Language Models (LLMs) and Generative AI to solve complex, real-world problems. If you are passionate about the future of AI and want to work in a cutting-edge environment, we want to hear from you.


Why Join Us?

  • Work with state-of-the-art infrastructure and proprietary data sets.
  • Competitive equity package and benefits.
  • Flexible remote-first culture with offices in SF and NYC.

Responsibilities

  • Model Development: Design, train, and fine-tune large-scale generative models using PyTorch and TensorFlow to optimize for performance and accuracy.
  • MLOps Architecture: Build scalable MLOps pipelines to automate model training, deployment, and monitoring in production environments.
  • Research & Innovation: Stay abreast of the latest AI research (e.g., from NeurIPS, ICML) and implement novel techniques to improve model reasoning and hallucination reduction.
  • Collaboration: Partner with product managers, data scientists, and software engineers to integrate AI capabilities into user-facing products seamlessly.
  • Ethical AI: Ensure AI systems adhere to ethical guidelines, safety protocols, and bias mitigation strategies.

Qualifications

  • Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field (4+ years of experience with a Bachelor’s degree).
  • Technical Skills: Strong proficiency in Python, SQL, and deep learning frameworks (PyTorch, TensorFlow, JAX).
  • Experience: 5+ years of professional experience in AI/ML engineering, specifically with LLMs and NLP.
  • Tools: Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
  • Problem Solving: Demonstrated ability to debug complex distributed systems and optimize inference latency.

Required Skills

Python PyTorch TensorFlow MLOps Machine Learning NLP LLM Generative AI Docker Kubernetes AWS Data Science AI Engineering

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