Job Description
Shape the Future of Intelligence.
We are seeking a visionary AI Research Scientist to lead our 2026 Trajectory Initiative. In this pivotal role, you will define the architectural roadmap for next-generation autonomous agents and generative systems, bridging the gap between theoretical breakthroughs and scalable industrial applications.
At Apex Future Labs, we aren't just building software for today; we are architecting the intelligence layer for the enterprise of 2026 and beyond. You will work at the intersection of Neuromorphic Computing, Large Language Models (LLMs), and Autonomous Decision Frameworks.
Why Join Us?
- Impactful Work: Directly influence the strategic direction of our flagship AI products.
- Top-Tier Talent: Collaborate with world-renowned experts in Deep Learning and Cognitive Science.
- Future-Ready: Focus on technologies predicted to dominate the market in 2026.
If you are passionate about pushing the boundaries of what is possible in Artificial General Intelligence (AGI) and are ready to lead the charge into the future, we want to hear from you.
Responsibilities
- Lead Research Strategy: Design and execute high-impact research projects focused on the development of Agentic AI systems capable of autonomous problem-solving by 2026.
- Model Architecture: Architect and fine-tune proprietary foundation models, specializing in multimodal learning and reinforcement learning from human feedback (RLHF).
- Prototyping & Validation: Build scalable prototypes for internal testing and external pilot programs, ensuring robustness, safety, and efficiency.
- Technical Leadership: Mentor a team of junior data scientists and engineers, fostering a culture of innovation and rigorous scientific inquiry.
- Industry Collaboration: Publish findings in top-tier conferences (NeurIPS, ICML, ICLR) and establish partnerships with leading research institutions.
- Product Translation: Translate complex research findings into clear, actionable technical specifications for our engineering and product teams.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Physics, or a related field with a focus on Artificial Intelligence.
- Experience: Minimum of 7+ years of experience in AI/ML research or applied machine learning engineering.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (Ray, Spark).
- Modeling: Strong background in Deep Learning, Natural Language Processing (NLP), and Large Language Models (LLMs).
- Innovation: Demonstrated history of publishing patents or research papers in AI-related fields.
- Strategic Mindset: Ability to align technical research goals with long-term business objectives and the specific 2026 roadmap.