Job Description
Are you ready to engineer the future of intelligence?
Nexus Horizon Labs is pioneering the next generation of autonomous systems and generative AI. We are seeking a visionary Senior AI/ML Engineer to join our elite team and shape the technology landscape for the 2026 horizon. In this role, you will design and deploy cutting-edge models that push the boundaries of what is possible, working on high-impact projects that redefine industry standards.
Why Join Us?
- Work on mission-critical AI infrastructure.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to the latest hardware and cloud resources for research.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art deep learning models, including LLMs and computer vision systems, to solve complex business problems.
- Infrastructure Scaling: Build robust MLOps pipelines to deploy models to production environments, ensuring high availability, latency optimization, and security.
- Research & Innovation: Stay ahead of the curve by researching emerging AI paradigms and methodologies applicable to the 2026 technological landscape.
- Data Strategy: Partner with data scientists and engineers to curate high-quality datasets and implement effective feature engineering strategies.
- Code Review & Mentorship: Lead code reviews, conduct technical architecture discussions, and mentor junior engineers to foster a culture of excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related field.
- Experience: 5+ years of professional experience in machine learning engineering or applied research.
- Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, and SQL.
- Frameworks: Proven experience with Hugging Face Transformers, LangChain, and cloud ML platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
- Problem Solving: Deep understanding of statistical learning, NLP, or Reinforcement Learning principles.
- Soft Skills: Exceptional communication skills with the ability to translate complex technical concepts for diverse stakeholders.