Job Description
Join Apex Digital Horizons as our next 2026 Visionary AI Engineer. We are not just building software for today; we are architecting the intelligent systems that will define the technological landscape of 2026 and beyond. In this role, you will spearhead the development of next-generation Generative AI models, Autonomous Agents, and scalable Neural Architectures designed to solve complex, unsolved problems in enterprise automation and creative intelligence.
You will work in a high-performance environment where innovation is the currency. We are looking for someone who doesn't just follow trends but anticipates the future of Artificial General Intelligence (AGI) integration into daily workflows. If you have a passion for pushing the boundaries of Deep Learning and a desire to leave a legacy in the tech stack of tomorrow, we want to hear from you.
You will work in a high-performance environment where innovation is the currency. We are looking for someone who doesn't just follow trends but anticipates the future of Artificial General Intelligence (AGI) integration into daily workflows. If you have a passion for pushing the boundaries of Deep Learning and a desire to leave a legacy in the tech stack of tomorrow, we want to hear from you.
Responsibilities
- Design, train, and deploy state-of-the-art Large Language Models (LLMs) and Diffusion Models optimized for production scalability.
- Architect robust Retrieval-Augmented Generation (RAG) pipelines to ensure data integrity and reduce hallucinations.
- Optimize model inference latency and throughput using advanced quantization and distributed computing techniques.
- Lead the research and implementation of ethical AI frameworks, ensuring bias mitigation and responsible deployment.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate technical requirements into cutting-edge features.
- Conduct rigorous code reviews and mentor junior engineers in best practices for machine learning engineering.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Minimum of 5 years of professional experience in Machine Learning Engineering, with a strong portfolio of deployed models.
- Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
- Extensive experience working with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Proven track record of implementing MLOps pipelines and CI/CD for machine learning models.
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning concepts.