Job Description
Are you ready to engineer the future? Quantum Leap Technologies is seeking a visionary Senior AI/ML Engineer to join our elite team in San Francisco. We are at the forefront of defining the technological landscape for 2026 and beyond, specializing in scalable generative AI, natural language processing, and autonomous systems.
In this role, you will not just implement existing models; you will architect the neural architectures that will power the next generation of enterprise solutions. If you are passionate about pushing the boundaries of artificial intelligence and want to work with a team of industry leaders, this is your opportunity to make a significant impact.
Why Join Us?
- Work on cutting-edge projects that shape the future of tech.
- Competitive compensation package and equity options.
- Flexible remote-first hybrid work culture.
- Access to state-of-the-art computing infrastructure.
We are looking for a self-starter who thrives in a fast-paced, innovative environment.
Responsibilities
- Design, develop, and deploy scalable machine learning models and AI systems using Python, TensorFlow, and PyTorch.
- Lead the end-to-end machine learning lifecycle, from data ingestion and preprocessing to model training, evaluation, and productionization.
- Collaborate with cross-functional product and engineering teams to translate complex business requirements into robust AI solutions.
- Optimize existing algorithms for high performance, low latency, and reduced computational costs.
- Stay at the forefront of AI research and implement novel techniques to improve system capabilities.
- Mentor junior engineers and contribute to the technical roadmap for future AI initiatives.
- Ensure model reliability, interpretability, and ethical AI compliance across all projects.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience).
- Minimum of 5+ years of professional experience in AI/ML engineering, with a strong portfolio of deployed models.
- Proficient in Python and modern machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
- Deep understanding of statistical modeling, natural language processing (NLP), and deep learning architectures.
- Experience with big data technologies (Spark, Hadoop) and cloud platforms (AWS, GCP, or Azure).
- Strong problem-solving skills and the ability to work independently in a fast-paced, ambiguous environment.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.