Job Description
Join the Architects of Tomorrow.
Quantum Leap Dynamics is seeking a visionary Senior AI/ML Engineer to spearhead our 'Vision 2026' initiative. We are building the foundational infrastructure for the next generation of generative AI and autonomous systems. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and predictive analytics, this is your opportunity to shape the future of technology.
In this role, you will design scalable machine learning pipelines, mentor junior engineers, and collaborate with cross-functional teams to deploy cutting-edge solutions. You will work in a fast-paced, innovative environment where your code will have a tangible impact on industries ranging from healthcare to fintech.
Why Join Us?
- Future-Proof Your Career: Work on projects that define the roadmap for 2026 and beyond.
- Competitive Compensation: We offer a top-tier salary package plus performance bonuses.
- Remote-First Culture: Enjoy the flexibility of working from anywhere in the US.
- Continuous Learning: Access to the latest GPUs, cloud resources, and conferences.
Responsibilities
- Design, develop, and deploy scalable machine learning models and NLP solutions tailored for the 'Vision 2026' roadmap.
- Optimize existing algorithms to improve latency, throughput, and accuracy in production environments.
- Collaborate with data scientists and software engineers to integrate AI models into broader application architectures.
- Mentor team members on best practices in MLOps, model training, and evaluation.
- Conduct research to identify new AI techniques and technologies that can be leveraged for competitive advantage.
- Ensure data privacy, security, and ethical AI compliance across all projects.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Minimum of 5+ years of experience in AI/ML engineering with a focus on NLP or Deep Learning.
- Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Experience deploying models via REST APIs and integrating them into frontend applications.
- Deep understanding of MLOps principles and model lifecycle management.
- Exceptional problem-solving skills and the ability to work in a high-velocity, ambiguous environment.