Job Description
We are at the precipice of a technological paradigm shift. Apex Future Systems is pioneering the infrastructure for the 2026 AI Era, and we need a visionary Senior AI/ML Architect to lead our research and engineering initiatives. You will be responsible for designing scalable, fault-tolerant systems that power the next generation of generative intelligence. If you are obsessed with pushing the boundaries of what is possible in machine learning and want to define the standard for 2026 and beyond, we want to hear from you.
The Opportunity
In this role, you will bridge the gap between theoretical research and production-grade engineering. You will work directly with C-level leadership to roadmap our AI capabilities, ensuring our platforms are not just functional, but revolutionary. Join a team of elite engineers and data scientists building the future of human-computer interaction.
Responsibilities
- Architect the 2026 Roadmap: Define the long-term technical vision for our AI infrastructure, focusing on scalability, security, and state-of-the-art model performance.
- Design Scalable Pipelines: Build robust, high-throughput data pipelines and model serving architectures capable of handling petabyte-scale data processing.
- Optimize Performance: Deep dive into model inference optimization, including quantization, pruning, and distributed training strategies to reduce latency and costs.
- Lead Technical Innovation: Conduct research into emerging AI paradigms (e.g., Multimodal AI, Autonomous Agents) and prototype solutions that can be integrated into our core products.
- Mentor & Empower: Foster a culture of technical excellence by mentoring junior architects and engineers, conducting code reviews, and establishing engineering best practices.
- Collaborate Cross-Functionally: Partner with product managers, designers, and data scientists to translate complex business requirements into elegant technical solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 10+ years of experience in software engineering and machine learning, with at least 5 years in a senior architectural or lead engineering role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Deep understanding of distributed systems (Kubernetes, Docker, Apache Spark).
- AI Expertise: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning. Experience with LLMs (Large Language Models) is highly preferred.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems with creative, data-driven solutions.
- Leadership: Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.