Job Description
Join the Future of Intelligence at Apex Neural Systems
We are seeking a visionary Senior Machine Learning Engineer to lead the next generation of AI infrastructure. If you are passionate about building scalable, robust, and transformative machine learning models that solve real-world problems, we want to hear from you. You will be working in the heart of the San Francisco tech hub, collaborating with world-class researchers and engineers.
Why Join Us?
- Impact: Build systems that will define the AI landscape for the next decade.
- Culture: A diverse, inclusive environment focused on innovation and continuous learning.
- Perks: Top-tier health benefits, equity packages, and flexible remote/hybrid work options.
Responsibilities
- Model Development: Design, train, and deploy advanced machine learning and deep learning models using Python and modern frameworks.
- System Architecture: Architect scalable MLOps pipelines that facilitate data ingestion, model training, and real-time inference.
- Optimization: Continuously optimize model performance, reducing latency and increasing throughput for production environments.
- Research & Innovation: Stay at the forefront of AI research, experimenting with new architectures (e.g., Transformers, Graph Neural Networks) to improve system capabilities.
- Collaboration: Work closely with data scientists and software engineers to integrate AI models into broader product ecosystems.
- Leadership: Mentor junior engineers and provide technical guidance on best practices for data handling and model governance.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Statistics, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years leading complex projects.
- Technical Skills: Proficiency in Python (PyTorch, TensorFlow, JAX) and SQL. Experience with cloud platforms (AWS, GCP, or Azure).
- MLOps: Strong understanding of CI/CD, containerization (Docker, Kubernetes), and MLOps tools (MLflow, Kubeflow).
- Mathematics: Solid foundation in linear algebra, calculus, and probability/statistics.
- Communication: Excellent verbal and written communication skills, capable of translating complex technical concepts for diverse audiences.