Job Description
Are you ready to define the future of technology?
Apex Horizon Systems is at the forefront of the next technological revolution. We are seeking a visionary Lead AI & Machine Learning Engineer to join our elite R&D division. In this role, you won't just be maintaining legacy systems; you will architect the intelligent core of our products that will dominate the landscape by 2026.
As a pioneer in our field, you will leverage cutting-edge generative models, scalable distributed systems, and ethical AI frameworks to solve complex, global challenges. If you thrive in a high-velocity, innovative environment and want to leave a permanent mark on the industry, this is your stage.
Why Join Us?
- Work on groundbreaking projects that redefine user interaction.
- Competitive compensation and equity packages for top performers.
- Access to the latest hardware and cloud infrastructure.
- A culture that prioritizes continuous learning and mentorship.
Responsibilities
- Architect and deploy scalable, high-performance machine learning models for real-time applications.
- Lead research initiatives into emerging AI paradigms, including Large Language Models (LLMs) and computer vision.
- Collaborate with cross-functional teams of product managers, designers, and engineers to translate business requirements into technical solutions.
- Optimize model inference and training pipelines to reduce latency and improve cost-efficiency.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and innovation.
- Ensure all AI systems adhere to strict ethical guidelines, data privacy standards, and regulatory compliance.
Qualifications
- Master’s or PhD in Computer Science, Statistics, Mathematics, or a related field (or equivalent practical experience).
- 7+ years of professional experience in Machine Learning, with at least 2 years in a lead or senior engineering capacity.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying production-grade ML models serving millions of users.
- Strong understanding of distributed computing systems (Kubernetes, AWS, GCP, or Azure).
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.