Job Description
We are seeking a visionary Senior AI/ML Engineer to join our elite R&D division in San Francisco. At QuantumLeap Systems, we are pioneering the next generation of generative intelligence and autonomous systems. You will work at the forefront of technology, leveraging cutting-edge algorithms to solve complex problems that shape the future of human-computer interaction.
Our ideal candidate is not just an expert in code, but a thought leader who thrives in a fast-paced, innovative environment. If you are passionate about Large Language Models (LLMs), computer vision, and scalable architecture, we want to hear from you.
Responsibilities
- Model Development: Design, train, and fine-tune state-of-the-art deep learning models, including Transformers and diffusion models, to enhance product performance.
- Infrastructure Optimization: Build and maintain robust, scalable ML pipelines using modern cloud infrastructure (AWS/GCP) and containerization technologies (Docker/Kubernetes).
- Research & Innovation: Stay abreast of the latest research in the AI field and implement novel techniques to improve model accuracy and efficiency.
- Collaboration: Partner with cross-functional teams of data scientists, software engineers, and product managers to define technical requirements and deliver high-impact features.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning within the team.
- Deployment: Oversee the end-to-end deployment of AI models into production environments, ensuring reliability and low-latency inference.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: Minimum 5+ years of experience in machine learning, deep learning, or natural language processing.
- Technical Skills: Proficiency in Python, PyTorch or TensorFlow, and experience with MLOps tools (MLflow, Kubeflow, etc.).
- Domain Knowledge: Strong understanding of statistical modeling, neural network architectures, and optimization techniques.
- Communication: Excellent written and verbal communication skills, with the ability to translate complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver innovative solutions under tight deadlines.