Job Description
Are you ready to define the technological trajectory for 2026? Apex Innovation Systems is seeking a visionary Senior AI & Machine Learning Architect to join our elite R&D team. We are building the next generation of autonomous systems and are looking for a leader who thrives on complexity and innovation.
In this role, you will be at the forefront of integrating cutting-edge Generative AI and predictive analytics into our core infrastructure. You won't just maintain legacy systems; you will architect the future of how our clients interact with data. If you are passionate about building scalable, high-impact AI solutions and want to leave a legacy in the tech landscape, we want to hear from you.
Why Join Us?
- Work on future-proof technologies designed for the 2026 market landscape.
- Competitive compensation package with performance bonuses.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to mentor the next generation of AI engineers.
Responsibilities
- Architect Design: Lead the end-to-end design and implementation of scalable machine learning models and deep learning pipelines.
- Innovation Leadership: Spearhead research into emerging AI methodologies, specifically focusing on LLMs and Computer Vision for the 2026 roadmap.
- System Optimization: Drive the optimization of data processing workflows to ensure sub-millisecond latency and high throughput.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and software engineers to translate business requirements into technical architectures.
- Code Quality: Establish and enforce best practices for code reviews, testing, and deployment automation within the AI team.
- Technical Mentorship: Mentor junior developers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in Machine Learning Engineering, with at least 2 years in a lead or architect role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and SQL.
- Cloud Expertise: Deep understanding of cloud-native architectures (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Domain Knowledge: Strong background in NLP, Reinforcement Learning, or Generative AI models.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.