Job Description
We are seeking a visionary 2026 AI & Machine Learning Engineer to join Apex Horizon Systems. In this pivotal role, you will architect the foundational models that will define the technological landscape of the coming decade. We are not just building software; we are engineering the future.
As a leader in next-generation artificial intelligence, we are looking for individuals who thrive in ambiguity and are passionate about solving complex problems at scale. You will work alongside world-class researchers and engineers to deploy state-of-the-art models into production environments.
Why join us?
- Work on cutting-edge Generative AI and Predictive Analytics.
- Competitive equity and comprehensive benefits package.
- Flexible remote-first policy with a focus on collaboration.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale machine learning models using Python and modern deep learning frameworks (PyTorch/TensorFlow).
- System Architecture: Design scalable, fault-tolerant systems for model inference and data processing pipelines.
- Research: Stay abreast of the latest research in Natural Language Processing (NLP) and Computer Vision to implement novel algorithms.
- Optimization: Optimize model performance for speed and accuracy, reducing latency in real-time applications.
- Collaboration: Partner with product managers and data scientists to translate business requirements into technical solutions.
- Mentorship: Guide junior engineers and contribute to a culture of continuous learning and innovation.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: 5+ years of professional experience in software engineering and machine learning.
- Programming: Proficiency in Python, with experience in C++ or Java for high-performance computing.
- Frameworks: Deep understanding of PyTorch, TensorFlow, or JAX.
- Algorithms: Strong grasp of statistical modeling, optimization techniques, and distributed systems.
- Tools: Experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker/Kubernetes).