Job Description
Are you ready to shape the future of intelligent systems? Apex Innovations is seeking a visionary Senior AI Engineer to lead our cutting-edge Generative AI and Large Language Model (LLM) initiatives. As a leader in the tech sector, we are committed to pushing the boundaries of artificial intelligence to create solutions that impact millions.
In this role, you will architect scalable AI solutions, mentor a talented team of data scientists, and drive the deployment of state-of-the-art models. If you are passionate about the intersection of data, mathematics, and real-world applications, we want to hear from you.
Why Join Us?
- Competitive Compensation: Salary up to $260k + Equity.
- Remote-First Culture: Work from anywhere in the US.
- Top-Tier Tech Stack: Access to the latest GPUs and cloud infrastructure.
- Professional Growth: Continuous learning budget and conference attendance.
Responsibilities
- Design, develop, and deploy advanced machine learning models, with a focus on Generative AI and NLP.
- Optimize inference pipelines for latency and cost efficiency in production environments.
- Collaborate with cross-functional teams (Product, Engineering, Design) to define AI product requirements.
- Conduct research to stay abreast of the latest advancements in deep learning and transformer architectures.
- Implement MLOps best practices to ensure model reproducibility and monitoring.
- Guide and mentor junior engineers and data scientists on complex technical challenges.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Expert proficiency in Python and frameworks such as PyTorch or TensorFlow.
- Proven experience working with Large Language Models (LLMs), RAG architectures, and fine-tuning techniques.
- Strong understanding of distributed systems, cloud computing (AWS/GCP), and containerization (Docker/Kubernetes).
- Experience with model evaluation, A/B testing, and productionizing ML models.