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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI/ML Engineer

Horizon Nexus
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
31 Mei 2026
Deadline
31 Mei 2027

Job Description

About Horizon Nexus: We are the architects of the 2026 digital landscape. We are a premier technology firm specializing in next-generation Artificial Intelligence, Generative Models, and Spatial Computing. Our mission is to solve humanity's most complex challenges through scalable, ethical, and innovative AI solutions. We are looking for a visionary Senior AI/ML Engineer to join our elite R&D division and help define the future of machine intelligence.

Why Join Us?

  • Impactful Work: Build core infrastructure that powers the next generation of autonomous systems.
  • Future-Ready Tech: Work with cutting-edge tools including PyTorch 2.0, LLaMA 3, and Quantum-Ready algorithms.
  • Competitive Compensation: Top-tier salary, equity, and comprehensive benefits package.

Responsibilities

  • Architect LLM Pipelines: Design, train, and deploy large-scale generative models tailored for enterprise applications.
  • Roadmap Leadership: Define the technical roadmap for our 2026 AI initiatives, focusing on efficiency and hallucination reduction.
  • Model Optimization: Implement quantization, pruning, and distributed training strategies to reduce inference costs.
  • MLOps Implementation: Build robust CI/CD pipelines for model deployment using Kubernetes and Docker.
  • Cross-Functional Collaboration: Partner with product teams to translate complex AI capabilities into user-centric features.
  • Research & Innovation: Stay ahead of the curve by researching emerging paradigms such as Multimodal AI and Agentic workflows.

Qualifications

  • Education: Master’s or PhD in Computer Science, Mathematics, or a related field.
  • Experience: 5+ years of professional experience in AI/ML engineering, with a focus on Deep Learning.
  • Programming: Expert proficiency in Python (PyTorch, TensorFlow, JAX) and SQL.
  • Frameworks: Strong understanding of Hugging Face Transformers, LangChain, and RAG architectures.
  • Deployment: Experience with cloud platforms (AWS/GCP/Azure) and MLOps tools (MLflow, Kubeflow, SageMaker).
  • Soft Skills: Exceptional problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.

Required Skills

Python PyTorch TensorFlow Deep Learning NLP LLM MLOps AWS Kubernetes Generative AI GPT Machine Learning SQL Docker

Ready to Take This Challenge?

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