Job Description
Are you ready to shape the future of intelligent systems? Apex Data Systems is seeking a visionary Senior AI Engineer to join our elite team in San Francisco. We are building next-generation neural networks that redefine user interaction and operational efficiency. If you thrive in a fast-paced, high-impact environment and want to lead the charge in AI innovation, this is your opportunity.
We are looking for a technical leader who doesn't just write code, but architects the future. You will work on cutting-edge projects involving Natural Language Processing (NLP), Computer Vision, and predictive analytics. Join us and be part of a culture that values curiosity, technical excellence, and bold ideas.
Responsibilities
- Model Development & Deployment: Design, train, and deploy scalable machine learning models and deep learning architectures from prototype to production.
- System Optimization: Continuously optimize existing models for speed, accuracy, and resource efficiency to ensure real-time performance.
- Research & Innovation: Conduct cutting-edge research to identify new opportunities for AI application within our product suite and industry verticals.
- Collaboration: Partner with cross-functional teamsâincluding data scientists, product managers, and software engineersâto integrate AI solutions seamlessly.
- Mentorship: Mentor junior engineers and contribute to code reviews, architectural decisions, and technical documentation.
- Infrastructure: Manage the end-to-end ML pipeline, including data ingestion, processing, storage, and model serving using cloud technologies.
Qualifications
- Education: PhD or Masterâs degree in Computer Science, Mathematics, Statistics, or a related field.
- Experience: Minimum of 5 years of professional experience in AI/ML engineering, with a proven track record of shipping production-grade models.
- Technical Skills: Strong proficiency in Python, PyTorch, TensorFlow, and Scikit-learn. Experience with MLOps tools (Kubeflow, MLflow) and containerization (Docker, Kubernetes).
- Domain Knowledge: Deep understanding of deep learning architectures, NLP, or Computer Vision. Experience with LLMs (Large Language Models) is a strong plus.
- Big Data: Experience working with big data technologies (Apache Spark, Hadoop) and distributed computing frameworks.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.