Job Description
Are you ready to build the intelligence that will define the world of 2026? NexaCore Technologies is pioneering the next generation of Artificial General Intelligence (AGI). We are seeking a visionary AI/ML Architect to lead our research and deployment teams in designing systems that push the boundaries of human capability.
In this high-impact role, you won't just be writing code; you will architect the neural pathways of the future. You will work with a world-class team of data scientists, engineers, and futurists to deliver scalable, ethical, and revolutionary AI solutions.
Why Join Us?
- Shape the Future: Directly influence the roadmap for 2026 and beyond.
- Elite Team: Collaborate with top-tier talent from Stanford, MIT, and Google DeepMind.
- Generous Compensation: Competitive base salary plus performance equity.
- Flexible Culture: Remote-first with access to state-of-the-art San Francisco hubs.
The Role:
We are looking for a leader who bridges the gap between theoretical research and production-grade engineering. You will be responsible for the end-to-end lifecycle of our AI models, ensuring they are robust, efficient, and scalable for global deployment.
Responsibilities
- Architect Next-Gen Systems: Design and implement scalable machine learning infrastructure tailored for the demands of 2026 and beyond.
- Model Research & Development: Spearhead the development of cutting-edge algorithms in Natural Language Processing (NLP) and Computer Vision.
- Production Deployment: Oversee the transition of models from research environments to high-volume production systems using containerization and orchestration.
- Performance Optimization: Continuously monitor, evaluate, and optimize model latency, accuracy, and resource consumption.
- Mentorship: Lead and mentor a team of junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- AI Ethics: Ensure all deployed models adhere to strict ethical guidelines and safety protocols.
- Stakeholder Communication: Translate complex technical concepts into clear strategies for executive leadership and non-technical stakeholders.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
- Experience: 5+ years of experience in Machine Learning Engineering or Applied AI, with at least 2 years in a leadership or architectural role.
- Core Tech Stack: Proficiency in Python, PyTorch, TensorFlow, and modern GPU computing frameworks (CUDA, cuDNN).
- System Design: Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and microservices.
- Data Engineering: Experience with big data technologies (Kafka, Spark, Hadoop) and data pipeline optimization.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems with innovative technical solutions.
- Communication: Exceptional verbal and written communication skills in English.