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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI & Machine Learning Engineer

Nexus Future Tech
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

Build the Future of Intelligence

Join Nexus Future Tech as a Senior AI & Machine Learning Engineer and help define the technological landscape for the year 2026. We are at the forefront of generative AI, working on scalable models that power next-generation applications.

As a key member of our AI division, you will bridge the gap between theoretical research and production-grade engineering. You will work in a fast-paced environment where your code impacts millions of users globally.

Why Join Us?

  • Work with cutting-edge technologies like LLMs, Transformers, and Reinforcement Learning.
  • Competitive equity and salary packages.
  • Flexible remote-first culture with a hub in the heart of San Francisco.

Responsibilities

  • Model Development: Design, train, and fine-tune state-of-the-art machine learning models for NLP and computer vision tasks.
  • Production Deployment: Engineer scalable AI solutions using MLOps best practices to deploy models into high-traffic production environments.
  • Optimization: Optimize model inference latency and reduce computational costs using techniques like quantization and distillation.
  • Data Strategy: Collaborate with data engineering teams to build robust data pipelines and ensure high-quality training data.
  • Research & Innovation: Stay abreast of the latest academic papers and industry trends to implement novel algorithms.
  • Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.

Qualifications

  • Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
  • Experience: 5+ years of professional experience in machine learning or AI engineering.
  • Programming: Expert proficiency in Python, with strong knowledge of PyTorch, TensorFlow, or JAX.
  • Algorithms: Deep understanding of classical and modern ML algorithms, neural networks, and statistical methods.
  • Tools: Experience with cloud platforms (AWS/GCP/Azure), Kubernetes, and version control (Git).
  • Communication: Excellent ability to communicate complex technical concepts to both technical and non-technical stakeholders.

Required Skills

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

Ready to Take This Challenge?

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