Job Description
Are you ready to engineer the future of intelligence? OmniCorp Future Systems is looking for a world-class Senior AI Engineer to join our forward-thinking team. We are building the next generation of generative models and autonomous agents, and we need a visionary engineer to lead our core infrastructure.
In this role, you will not just write code; you will define the architectural standards for AI deployment at scale. If you are passionate about Large Language Models (LLMs), computer vision, or predictive analytics, and you thrive in a cutting-edge environment, we want to meet you.
What You'll Do:
- Lead the development and optimization of state-of-the-art machine learning models.
- Design robust MLOps pipelines to ensure high availability and scalability.
- Collaborate with cross-functional teams to integrate AI capabilities into consumer products.
- Conduct research to stay ahead of industry trends and implement innovative solutions.
Responsibilities
- Model Development: Design, train, and fine-tune complex deep learning models to solve real-world business problems.
- System Architecture: Build scalable microservices and APIs to serve AI models efficiently with low latency.
- Data Engineering: Work with massive datasets to perform data cleaning, augmentation, and feature engineering.
- Performance Tuning: Continuously monitor model accuracy and system performance, implementing optimizations as needed.
- Best Practices: Enforce coding standards, documentation, and testing protocols across the engineering department.
- Innovation: Explore new frameworks (e.g., PyTorch, TensorFlow, JAX) and contribute to open-source projects.
Qualifications
- Education: Master’s degree in Computer Science, AI, or a related quantitative field (PhD preferred).
- Experience: 5+ years of professional experience in software engineering and machine learning.
- Programming: Deep expertise in Python, C++, or Java with strong proficiency in data manipulation libraries (Pandas, NumPy).
- Frameworks: Proven experience with deep learning frameworks such as PyTorch or TensorFlow.
- Cloud & DevOps: Experience deploying models on cloud platforms (AWS, GCP, or Azure) using Docker and Kubernetes.
- Problem Solving: Strong analytical skills with a track record of delivering high-impact technical solutions.