Job Description
Are you ready to shape the future? Apex Innovations is looking for a visionary Senior AI Engineer to lead the architecture and development of Project 2026, our flagship initiative aimed at revolutionizing generative AI infrastructure for enterprise scalability.
Join our elite R&D team in the heart of San Francisco. You will be responsible for building the foundational models and neural networks that will power our platform for the next decade. If you thrive in a fast-paced, high-impact environment and want to work on cutting-edge technology, this is your opportunity.
The Role
As the Senior AI Engineer, you will bridge the gap between theoretical machine learning research and production-grade software engineering. You will define the technical vision for Project 2026, ensuring our models are not only accurate but also efficient, secure, and scalable.
Responsibilities
- Architectural Leadership: Design and implement scalable, high-performance AI systems and microservices for Project 2026.
- Model Development: Research, train, and fine-tune large language models (LLMs) and computer vision algorithms to meet specific business requirements.
- System Optimization: Continuously monitor and optimize model inference speed, latency, and resource utilization.
- Cross-Functional Collaboration: Work closely with product managers, data scientists, and backend engineers to translate business goals into technical solutions.
- Code Quality: Establish best practices for code review, testing, and deployment within the AI lifecycle.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Security & Compliance: Implement robust data governance and security protocols to protect sensitive user data.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in software engineering with a strong focus on Machine Learning or Artificial Intelligence.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Docker, Kubernetes, MLflow) is highly preferred.
- Specialization: Deep expertise in NLP, Transformers, or Reinforcement Learning is a significant plus.
- Cloud Expertise: Proven track record of deploying models on major cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Exceptional ability to troubleshoot complex technical problems and debug high-dimensional data issues.
- Communication: Strong verbal and written communication skills; able to explain complex technical concepts to non-technical stakeholders.