Job Description
Welcome to Nexus Horizon Labs, a pioneering force in next-generation autonomous systems. We are on a mission to define the technological landscape of 2026 and beyond. As a Senior AI/ML Engineer, you will not just implement existing models; you will architect the fundamental intelligence driving our next-generation products.
We are looking for a visionary leader who thrives in ambiguity and possesses the technical prowess to build scalable, ethical, and high-performance AI systems. If you are ready to shape the future of human-machine interaction, we want to hear from you.
Why Join Us?
- Next-Gen Focus: Work on cutting-edge Agentic AI and Autonomous Systems slated for our 2026 roadmap.
- Impactful Work: Your code will directly influence how millions interact with AI in the future.
- Elite Team: Collaborate with PhD researchers and industry veterans from top tech giants.
Are you ready to build the intelligence of tomorrow, today?
Responsibilities
- Design, develop, and deploy state-of-the-art Large Language Models (LLMs) and multimodal agents tailored for enterprise scalability.
- Lead the architecture of Retrieval-Augmented Generation (RAG) pipelines to ensure data accuracy and reduce hallucinations.
- Optimize model inference performance using quantization, distillation, and hardware acceleration (GPU/TPU).
- Implement rigorous evaluation frameworks and A/B testing strategies to measure model efficacy and safety.
- Collaborate with product and engineering teams to translate complex AI capabilities into user-friendly features.
- Mentor junior engineers and establish best practices for MLOps and Responsible AI.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD preferred.
- 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Expert proficiency in Python, PyTorch, or TensorFlow.
- Strong understanding of LLM architectures (GPT, Llama, Mistral) and fine-tuning methodologies.
- Experience with vector databases (Pinecone, Milvus) and orchestration tools (LangChain, LlamaIndex).
- Demonstrated track record of shipping production-grade ML models.