Job Description
Are you ready to architect the future of intelligent systems? Apex Future Labs is at the forefront of technological innovation, developing next-generation AI solutions that will define the landscape of 2026 and beyond. We are looking for a visionary Senior AI/ML Architect to lead our technical strategy and build scalable, robust machine learning infrastructures.
In this role, you won't just write code; you will design the backbone of our AI ecosystem. You will collaborate with world-class researchers and engineers to deploy cutting-edge models that power real-world applications. Join us in building the future of technology from the heart of Silicon Valley.
Responsibilities
- Architect & Design: Lead the end-to-end design and implementation of scalable machine learning pipelines and cloud infrastructure (AWS/Azure).
- Model Optimization: Drive research and development to optimize model accuracy, latency, and resource efficiency for production environments.
- Technical Leadership: Mentor junior engineers and data scientists, conducting code reviews and establishing best practices for AI development.
- Strategic Planning: Define the long-term technical roadmap for AI infrastructure, ensuring alignment with business goals and emerging industry trends.
- System Integration: Integrate complex AI models with existing software ecosystems and third-party APIs seamlessly.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to translate complex technical requirements into actionable development plans.
- Deployment & MLOps: Oversee the CI/CD pipelines for AI models, ensuring robust monitoring, logging, and automated retraining workflows.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 8+ years of experience in software engineering and 5+ years specifically in Machine Learning or AI Architecture.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and deep learning frameworks. Strong experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
- System Design: Proven track record of designing high-availability, distributed systems and large-scale data processing architectures.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.
- Problem Solving: Demonstrated ability to troubleshoot complex issues and innovate solutions in dynamic environments.
- Tools: Familiarity with MLOps tools (MLflow, Kubeflow) and version control (Git).