Job Description
We are at the forefront of the Artificial Intelligence revolution, defining the technological landscape of 2026. We are seeking a visionary Senior AI Engineer to architect the next generation of autonomous agents and generative AI models. If you are passionate about pushing the boundaries of Machine Learning and want to build the infrastructure that powers the future of human-computer interaction, we want to meet you.
At Apex Neural Systems, we don't just predict the future; we engineer it. You will work on cutting-edge projects involving Large Language Models (LLMs), reinforcement learning, and edge computing solutions designed for scalability and ethical AI deployment.
Why Join Us?
- Impactful Work: Build AI systems that will be used by millions.
- Top-Tier Compensation: Competitive salary, equity, and comprehensive benefits.
- Innovation: Access to the latest GPUs and cloud infrastructure.
- Remote-First Culture: Flexible work arrangements for top talent.
Responsibilities
- Architect & Deploy: Design and implement scalable machine learning pipelines and model serving architectures optimized for production environments.
- Model Innovation: Lead the research and development of proprietary AI models, focusing on generative capabilities and agent-based workflows for the 2026 roadmap.
- Optimization: Improve model inference speeds and accuracy through techniques such as quantization, pruning, and distillation.
- Collaboration: Partner with product managers and engineers to translate complex AI requirements into robust technical solutions.
- Ethical AI: Ensure all AI systems adhere to safety guidelines and ethical standards, addressing bias and fairness in training data.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent professional experience).
- Core Skills: Deep expertise in Python, PyTorch, or TensorFlow.
- Experience: 5+ years of professional experience in AI/ML engineering, specifically with LLMs and transformer architectures.
- Infrastructure: Strong understanding of MLOps, CI/CD, and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Proven track record of solving complex algorithmic problems in high-scale environments.
- Communication: Excellent ability to communicate technical concepts to non-technical stakeholders.