Job Description
Are you ready to architect the future of intelligence? Apex Innovation Labs is seeking a visionary Senior AI Engineer to lead our elite R&D division. In this pivotal role, you will define the roadmap for our next-generation models, pushing the boundaries of what is possible in 2026 and beyond.
We are looking for a technical mastermind who thrives in ambiguity and possesses a deep understanding of Large Language Models (LLMs), generative AI, and neural architecture search. If you are passionate about building scalable, ethical, and high-performance AI systems that will power the enterprises of tomorrow, we want to meet you.
Responsibilities
- Lead Model Development: Spearhead the design, training, and deployment of state-of-the-art deep learning models, specifically focusing on LLMs and generative architectures.
- Research & Innovation: Conduct cutting-edge research to explore new algorithms and architectures, publishing findings in top-tier conferences and journals.
- System Optimization: Optimize model inference and training pipelines to ensure high throughput, low latency, and cost-efficiency at scale.
- Collaboration: Work closely with product managers, data scientists, and engineering teams to translate complex AI concepts into production-ready solutions.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Deployment: Manage the end-to-end ML lifecycle, from data ingestion and feature engineering to model serving and monitoring.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Mathematics, Physics, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning, deep learning, or artificial intelligence.
- Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, or JAX. Deep experience with Hugging Face, LangChain, and Vector Databases (Pinecone, Milvus).
- System Knowledge: Hands-on experience with cloud infrastructure (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to solve complex technical problems and debug deep learning models effectively.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.