Job Description
The Future of Intelligence Awaits.
Are you ready to architect the breakthrough technologies that will define the year 2026? Nexus Future Labs is seeking a visionary Senior AI/ML Engineer to join our elite San Francisco team. We are not just building software; we are engineering the neural pathways of tomorrow. In this role, you will spearhead the development of next-generation artificial intelligence systems designed to solve complex, real-world problems at scale.
We are looking for a pioneer who thrives in ambiguity and possesses the technical prowess to turn abstract algorithms into tangible reality. If you are passionate about pushing the boundaries of what is possible with Large Language Models, Generative AI, and predictive analytics, this is your opportunity to lead the charge.
Why Nexus Future Labs?
• Be at the forefront of the 2026 technology roadmap.
• Work with state-of-the-art hardware and cloud infrastructure.
• Competitive equity and benefits package.
• Collaborative environment with industry leaders.
Responsibilities
- Architect & Deploy: Design, train, and deploy scalable machine learning models and deep learning architectures using Python and modern frameworks like PyTorch and TensorFlow.
- Research & Innovation: Conduct cutting-edge research in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning to stay ahead of the 2026 technology curve.
- Data Pipeline Optimization: Build robust MLOps pipelines to ensure efficient data ingestion, processing, and model versioning in production environments.
- Cross-Functional Leadership: Partner with product managers and engineering teams to translate business requirements into high-performance AI solutions.
- RAG & LLM Integration: Implement Retrieval-Augmented Generation (RAG) strategies and integrate Large Language Models (LLMs) into enterprise applications securely.
- Model Evaluation: Establish rigorous testing protocols and metrics to measure model accuracy, fairness, and performance drift over time.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, Statistics, or a related technical field (or equivalent practical experience).
- Experience: Minimum of 5+ years of professional experience in AI/ML engineering, with a proven track record of shipping production models.
- Technical Skills: Expert proficiency in Python, SQL, and experience with cloud platforms (AWS, GCP, or Azure).
- Frameworks: Deep familiarity with PyTorch, TensorFlow, Hugging Face Transformers, and Scikit-learn.
- Problem Solving: Strong analytical skills with the ability to debug complex system issues and optimize model inference latency.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and mentor junior engineers.