Job Description
Join Apex Horizon Tech as we define the future of Artificial Intelligence for the year 2026. We are a fast-paced, forward-thinking organization building scalable Generative AI solutions that are reshaping industries. As a Senior AI/ML Engineer, you won't just be writing code; you will be architecting the neural networks that power our next generation of intelligent products.
We are looking for a visionary engineer who thrives in ambiguity and has a passion for pushing the boundaries of Large Language Models (LLMs) and Computer Vision. You will work closely with our product and research teams to deploy state-of-the-art models into production environments.
Why join us?
- Work on cutting-edge projects that will define the tech landscape in 2026.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in San Francisco.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Model Architecture & Development: Design, train, and fine-tune complex machine learning models, specifically focusing on LLMs and transformer architectures for 2026-ready applications.
- Production Deployment: Build robust MLOps pipelines using Kubernetes and Docker to ensure high availability and scalability of AI models.
- Performance Optimization: Optimize model inference latency and accuracy to deliver real-time user experiences.
- Data Strategy: Collaborate with data engineering teams to curate high-quality training datasets and implement data governance protocols.
- Research & Innovation: Stay at the forefront of AI research, experimenting with new techniques such as Reinforcement Learning from Human Feedback (RLHF) and prompt engineering.
- Technical Leadership: Mentor junior engineers and conduct code reviews to maintain high engineering standards across the team.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field. PhD preferred.
- Experience: 5+ years of professional experience in Machine Learning and Deep Learning.
- Programming: Proficiency in Python, PyTorch, or TensorFlow.
- Tools: Experience with cloud platforms (AWS/GCP/Azure), SQL, and containerization technologies.
- Communication: Excellent verbal and written communication skills; ability to translate technical concepts for non-technical stakeholders.
- Passion: Deep interest in the future of AI and the ethical implications of machine learning technologies.