Job Description
Are you ready to shape the future of intelligent systems? Quantum Leap Innovations is seeking a visionary Senior AI Engineer to lead the next generation of machine learning models. We are building the infrastructure that will power the AI revolution of 2026 and beyond. If you are passionate about Generative AI, Large Language Models (LLMs), and scalable deep learning architectures, we want to meet you.
In this role, you will bridge the gap between cutting-edge research and production-grade software. You will be responsible for designing, training, and deploying complex models that solve real-world problems. Join a team of world-class engineers and data scientists who are redefining the boundaries of artificial intelligence.
Why Join Us?
- Work on ground-breaking projects that impact millions of users.
- Competitive compensation and equity packages.
- Flexible remote-first culture with premium health benefits.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art deep learning models, including Transformers and diffusion models.
- System Architecture: Architect scalable machine learning pipelines that handle high-throughput data ingestion and inference.
- MLOps: Implement and manage end-to-end MLOps workflows, including CI/CD, containerization, and model serving.
- Performance Optimization: Continuously optimize model accuracy and reduce inference latency for real-time applications.
- Research & Innovation: Stay at the forefront of the AI landscape, researching new techniques and integrating them into our product suite.
- Collaboration: Partner with product managers and engineers to translate business requirements into technical AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering or data science.
- Programming: Proficiency in Python, with deep expertise in PyTorch or TensorFlow.
- Frameworks: Strong understanding of Hugging Face Transformers, LangChain, and Scikit-learn.
- Cloud: Experience deploying models on cloud platforms such as AWS, GCP, or Azure.
- Problem Solving: Ability to debug complex distributed systems and optimize large-scale datasets.