Job Description
We are on a mission to define the technological landscape of 2026. At Nexus Horizon Labs, we aren't just building software; we are architecting the future of human-machine interaction. We are seeking a visionary Senior AI & Machine Learning Engineer to lead our "Future Tech" division.
In this role, you will work at the bleeding edge of Generative AI, Large Language Models, and predictive analytics. You will collaborate with a world-class team of data scientists, quantum researchers, and product strategists to build systems that are not only powerful but also ethical and scalable. If you are passionate about the trajectory of technology and want to leave a legacy in the industry, this is your opportunity.
Why Join Us?
- Work on cutting-edge projects that will shape the next decade of technology.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first culture with a premium office in downtown SF.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement robust, scalable machine learning pipelines for generative models and autonomous agents.
- Research & Development: Stay ahead of the curve with the latest advancements in AI research to integrate cutting-edge techniques into our core products.
- Model Optimization: Fine-tune large language models to improve efficiency, reduce latency, and enhance accuracy for enterprise use cases.
- Collaborative Innovation: Partner with cross-functional teams (Product, Engineering, Design) to translate complex technical requirements into user-centric solutions.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- System Reliability: Ensure the stability, security, and performance of deployed AI models in production environments.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field. Ph.D. is a plus.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Experience: 5+ years of experience in AI/ML engineering, specifically within deep learning or NLP.
- Tools: Strong familiarity with MLOps tools (e.g., MLflow, Kubeflow) and cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Exceptional ability to solve complex algorithmic problems and optimize system performance under pressure.
- Communication: Excellent written and verbal communication skills with the ability to explain technical concepts to non-technical stakeholders.