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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI & Machine Learning Engineer

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

Job Description

We are building the operating system for the future. As a leading enterprise focused on the technological horizon of 2026, Apex Future Systems is seeking a visionary Senior AI & Machine Learning Engineer to lead the development of our next-generation generative AI ecosystem. You will be at the intersection of cutting-edge research and scalable production engineering, working on models that will define the interaction between human intelligence and artificial intelligence.

Why Join Us?

  • Impact: Architect the AI infrastructure that powers our flagship product suite.
  • Innovation: Work with the latest in Large Language Models (LLMs) and generative transformers.
  • Equity: Competitive compensation package including stock options.

Responsibilities

  • Model Architecture: Design, train, and fine-tune large-scale transformer models for specific enterprise use cases.
  • Pipeline Optimization: Build and maintain high-throughput, low-latency inference pipelines using state-of-the-art serving technologies.
  • RAG Implementation: Develop advanced Retrieval-Augmented Generation architectures to ensure factual accuracy and context-awareness.
  • Collaboration: Partner with product managers and data scientists to translate complex business requirements into technical AI solutions.
  • MLOps: Establish robust CI/CD pipelines for model deployment, monitoring, and retraining cycles.

Qualifications

  • Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field.
  • Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years focusing on NLP and LLMs.
  • Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Frameworks: Deep experience with Hugging Face Transformers, LangChain, or LlamaIndex.
  • Cloud: Strong experience deploying models on AWS, GCP, or Azure using Kubernetes and Docker.

Required Skills

Python PyTorch TensorFlow Hugging Face LLM NLP MLOps Kubernetes Docker AWS GCP AI Machine Learning Generative AI

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