Job Description
We are building the intelligence layer for the future. As an AI/ML Architect specializing in the 2026 roadmap, you will lead the design and deployment of next-generation Generative AI models and autonomous agents. This is a rare opportunity to define the technology stack of tomorrow while solving complex, high-impact problems today.
At Apex Neural Systems, we don't just follow trends; we set them. You will work alongside world-class researchers and engineers to push the boundaries of Large Language Models (LLMs), ensuring scalability, efficiency, and ethical AI implementation.
Responsibilities
- Lead the architectural design and implementation of scalable MLOps pipelines for training and serving large-scale deep learning models.
- Optimize model inference latency and throughput for real-time Generative AI applications.
- Collaborate with research teams to fine-tune foundation models on proprietary datasets and implement RAG (Retrieval-Augmented Generation) architectures.
- Establish best practices for model monitoring, versioning, and continuous integration/deployment in a cloud-native environment.
- Drive the technical roadmap for 2026, evaluating emerging technologies such as multimodal learning and edge AI deployment.
- Debug complex distributed training scenarios and resolve hardware-software integration issues.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field (5+ years of industry experience).
- Deep expertise in Python, PyTorch, TensorFlow, and CUDA programming.
- Proven experience deploying LLMs (e.g., GPT-4, LLaMA) or similar Generative AI models to production environments.
- Strong proficiency in MLOps tools (Kubeflow, MLflow) and containerization technologies (Docker, Kubernetes).
- Experience with cloud platforms (AWS, GCP, or Azure) and serverless architectures.
- Excellent communication skills with the ability to translate technical concepts for cross-functional teams.