Job Description
We are seeking a visionary Senior AI/ML Engineer to join our elite engineering team in San Francisco. As we accelerate our roadmap towards 2026, we are looking for a technical leader who is passionate about building the future of intelligent systems. You will be responsible for designing, training, and deploying state-of-the-art machine learning models that power our core products.
In this role, you will collaborate with a diverse team of researchers and engineers to solve complex problems in Natural Language Processing (NLP) and Computer Vision. If you are driven by innovation and want to work on projects that define the next decade of technology, apply today.
Why Join Us?
• Competitive compensation package and equity.
• Cutting-edge technology stack and research opportunities.
• Flexible remote-first culture with a focus on work-life balance.
Responsibilities
- Model Development: Design, train, and optimize complex machine learning algorithms to support our 2026 product roadmap.
- System Architecture: Build scalable and robust MLOps pipelines to ensure seamless deployment and monitoring of models in production.
- Research & Innovation: Stay abreast of the latest advancements in Deep Learning and AI to implement novel solutions.
- Collaboration: Work closely with data scientists, backend engineers, and product managers to translate business requirements into technical specifications.
- Performance Optimization: Continuously monitor model performance and conduct rigorous testing to improve accuracy and latency.
- Code Quality: Write clean, maintainable, and well-documented code while adhering to industry best practices.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related technical field (or equivalent practical experience).
- Experience: 5+ years of professional experience in Machine Learning or Artificial Intelligence.
- Programming: Strong proficiency in Python and deep knowledge of frameworks such as TensorFlow, PyTorch, or JAX.
- MLOps: Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Tools: Familiarity with version control (Git), CI/CD pipelines, and data visualization tools (e.g., Tableau, Matplotlib).