Job Description
We are building the future of intelligent systems at Apex Horizon Technologies. As a leading innovator in the generative AI space, we are looking for a visionary Senior Engineer to lead our LLM initiatives. You will architect scalable solutions, fine-tune state-of-the-art models, and deploy them into production environments that redefine user experience.
Why join us?
We offer a competitive equity package, remote-first flexibility, and the chance to work on projects that impact millions of users globally. If you are passionate about the next generation of AI and want to push the boundaries of what's possible with Large Language Models, we want to meet you.
Responsibilities
- Model Engineering: Design, train, and fine-tune large language models (LLMs) using PyTorch and TensorFlow to optimize performance for specific enterprise use cases.
- RAG Architecture: Implement and optimize Retrieval-Augmented Generation pipelines to enhance model accuracy and reduce hallucinations.
- Deployment: Manage the end-to-end lifecycle of AI models, including containerization, CI/CD pipelines, and serverless deployment on AWS/GCP.
- Performance Optimization: Conduct rigorous testing and benchmarking to ensure low-latency inference and high throughput.
- Cross-Functional Leadership: Collaborate with product managers and data scientists to translate business requirements into technical AI solutions.
- Research: Stay ahead of the curve by integrating the latest research findings from top AI conferences into our production stack.
Qualifications
- Education: MS or PhD in Computer Science, Machine Learning, or a related quantitative field from a top-tier institution.
- Experience: 5+ years of professional software engineering experience, with at least 2 years dedicated to AI/ML or Deep Learning.
- Technical Skills: Strong proficiency in Python, C++, or Rust; deep understanding of Transformer architectures (BERT, GPT, LLaMA).
- Frameworks: Extensive experience with Hugging Face Transformers, LangChain, and model serving frameworks (vLLM, TGI).
- Infrastructure: Hands-on experience with cloud platforms (AWS/Azure/GCP) and GPU infrastructure management (NVIDIA).
- Problem Solving: Demonstrated ability to debug complex distributed systems and optimize resource-intensive algorithms.