Job Description
Are you ready to shape the future of intelligent systems? Apex Horizon Systems is seeking a visionary Senior Generative AI Engineer to join our elite engineering team in San Francisco. As we prepare to launch our next-generation LLM platform in 2026, you will be instrumental in building the architectural foundations that redefine human-computer interaction.
In this role, you will bridge the gap between cutting-edge research and scalable production systems. You will work with a diverse team of researchers, data scientists, and product managers to develop state-of-the-art language models, fine-tune large-scale transformers, and deploy robust MLOps pipelines.
Why join Apex Horizon?
- Work on projects that will impact millions of users.
- Competitive compensation package including equity.
- Flexible remote-first policy with a hub in the heart of SF.
Responsibilities
- Model Development: Design, train, and fine-tune large language models (LLMs) and multimodal AI systems using PyTorch and TensorFlow.
- Production Deployment: Engineer scalable MLOps pipelines to deploy models into high-traffic environments with a focus on latency, throughput, and cost efficiency.
- Research Integration: Stay at the forefront of AI research, evaluating and integrating novel techniques (e.g., RAG, LoRA, Reinforcement Learning from Human Feedback) into our products.
- System Optimization: Conduct rigorous performance benchmarking and optimization of inference engines to ensure real-time user experiences.
- Cross-Functional Leadership: Collaborate with product managers and designers to translate complex technical requirements into user-centric features.
Qualifications
- Education: Master’s or PhD degree 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 focused on Generative AI or Large Language Models.
- Technical Stack: Proficiency in Python, PyTorch, Hugging Face Transformers, and experience with vector databases (e.g., Pinecone, Milvus).
- Cloud & DevOps: Strong experience deploying models on AWS, GCP, or Azure using Docker, Kubernetes, and CI/CD pipelines.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and document architecture decisions.