Job Description
Are you ready to architect the future of intelligence? Apex Neural is seeking a visionary Lead AI Engineer to define the technology stack for the 2026 era. We are building the next generation of generative AI systems that will redefine human-machine interaction. If you are passionate about Large Language Models (LLMs), ethical AI, and scalable infrastructure, we want to meet you.
As a Lead AI Engineer at Apex Neural, you will bridge the gap between cutting-edge research and production-grade systems. You will lead a team of brilliant minds in designing, training, and deploying models that are not just smart, but safe, efficient, and transformative.
Responsibilities
- Model Architecture & Training: Design and implement state-of-the-art deep learning architectures for large-scale natural language processing and generative tasks.
- MLOps Pipeline Management: Build robust, automated MLOps pipelines using Kubernetes and Docker to ensure scalable model deployment and continuous integration.
- Performance Optimization: Optimize model inference speeds and reduce latency to enable real-time applications in high-traffic environments.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation, technical excellence, and ethical AI practices.
- R&D Collaboration: Work closely with the research team to translate theoretical advancements into practical, production-ready software solutions.
- Security & Compliance: Implement rigorous data governance and security protocols to protect proprietary datasets and ensure model fairness.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field; PhD preferred.
- Experience: 5+ years of experience in machine learning engineering, with at least 2 years in a lead or senior capacity.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep experience with Hugging Face Transformers and LLM fine-tuning.
- Infrastructure: Strong understanding of cloud platforms (AWS/GCP/Azure) and containerization technologies.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.
- Problem Solving: Proven track record of solving complex engineering challenges in high-stakes environments.