Job Description
Join Nexus Dynamics at the forefront of technological evolution as we pioneer solutions for 2026 and beyond. We're seeking an AI/ML Engineer to architect transformative systems that redefine industries. You'll collaborate with world-class researchers to deploy scalable machine learning models, leveraging cutting-edge frameworks to solve complex challenges in autonomous systems, predictive analytics, and generative AI. Our Austin hub offers an unparalleled environment where innovation meets impact, with competitive compensation, equity, and resources to accelerate your career.
As part of our elite engineering team, you'll shape the future of human-machine interaction while working on projects that directly influence global markets. We foster a culture of continuous learning and technical excellence, providing access to state-of-the-art infrastructure and industry partnerships. If you're passionate about pushing boundaries and building the technologies of tomorrow, this is your calling.
Responsibilities
- Design, develop, and deploy production-level AI/ML models using TensorFlow, PyTorch, and cloud-native architectures
- Lead end-to-end ML pipeline development from data ingestion to model optimization and deployment
- Collaborate with cross-functional teams to integrate AI solutions into autonomous systems and IoT platforms
- Research and implement novel approaches in generative AI, reinforcement learning, and multimodal systems
- Optimize model performance for edge computing and distributed environments
- Contribute to technical documentation and mentor junior engineers in ML best practices
- Stay current with emerging AI trends and evaluate their strategic impact on 2026 technology landscapes
Qualifications
- MS/PhD in Computer Science, AI, or related field with 5+ years of ML engineering experience
- Expert proficiency in Python, TensorFlow/PyTorch, and cloud platforms (AWS/GCP/Azure)
- Proven track record deploying scalable ML systems for production environments
- Strong foundation in distributed computing, MLOps, and model lifecycle management
- Experience with generative AI architectures (GANs, Transformers) and LLM fine-tuning
- Published research or open-source contributions in AI/ML domains preferred
- Ability to translate complex technical concepts into actionable business strategies
- Security-first approach to AI development with experience in ethical AI frameworks