Job Description
We are on a mission to build the foundational intelligence systems for the year 2026. As a Senior AI Architect at OmniVerse Tech, you will not just design algorithms; you will architect the future of human-machine interaction. You will lead a cross-functional team of engineers and researchers to define the technical strategy for our flagship AI product line, ensuring scalability, security, and ethical alignment.
Why Join Us?
- Shape the Future: Your work will directly define the roadmap for the 2026 launch cycle.
- Impactful Work: Build AI systems that solve complex global challenges.
- Top-Tier Compensation: Competitive salary and equity package.
- Flexible Environment: Hybrid work model supporting high-performance teams.
Responsibilities
- Technical Leadership: Define and execute the technical vision for AI infrastructure, guiding the team from research to production deployment for the 2026 cycle.
- System Architecture: Design scalable, fault-tolerant machine learning pipelines and data processing architectures using modern cloud-native technologies.
- Model Optimization: Lead initiatives to optimize Large Language Models (LLMs) and neural networks for real-time inference and reduced latency.
- Team Mentorship: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Strategic Roadmap: Collaborate with product managers to translate business requirements into technical blueprints and feasibility studies.
- Research Integration: Stay ahead of the curve by integrating cutting-edge research papers and novel architectures into our production stack.
- Ethical AI Compliance: Ensure all AI systems adhere to strict ethical guidelines and bias mitigation standards.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field.
- Experience: 5+ years of experience in software engineering with a focus on Artificial Intelligence and Machine Learning.
- Technical Skills: Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Architecture: Strong background in distributed systems, microservices, and cloud architecture (AWS, GCP, or Azure).
- Tools: Experience with MLOps tools such as Kubernetes, Docker, and MLflow.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated history of solving ambiguous problems with creative, scalable solutions.