Job Description
We are seeking a visionary Senior AI/ML Engineer to architect the intelligent systems of tomorrow. As we prepare for the next generation of AI in 2026, we need a technical leader to define the roadmap for our proprietary large language models and autonomous agents.
Why Join Nexus Horizon?
- Work on cutting-edge Generative AI and Predictive Analytics.
- Competitive compensation package with equity options.
- Flexible remote-first culture with quarterly in-person innovation sprints.
- Opportunity to shape the ethical standards of AI in the enterprise sector.
Key Responsibilities:
- Lead the end-to-end design and deployment of scalable machine learning pipelines.
- Optimize deep learning models for high-throughput, low-latency inference environments.
- Collaborate with product teams to integrate LLMs into consumer-facing applications.
- Establish best practices for data governance, model monitoring, and explainable AI (XAI).
- Mentor junior engineers and data scientists, fostering a culture of continuous learning.
Qualifications:
- B.S., M.S., or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in machine learning engineering and data science.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Proven track record of deploying models to production (AWS, GCP, or Azure).
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Excellent communication skills with the ability to translate technical concepts for diverse stakeholders.
Responsibilities
- Lead the end-to-end design and deployment of scalable machine learning pipelines.
- Optimize deep learning models for high-throughput, low-latency inference environments.
- Collaborate with product teams to integrate LLMs into consumer-facing applications.
- Establish best practices for data governance, model monitoring, and explainable AI (XAI).
- Mentor junior engineers and data scientists, fostering a culture of continuous learning.
Qualifications
- B.S., M.S., or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in machine learning engineering and data science.
- Expert proficiency in Python, PyTorch, and TensorFlow.
- Proven track record of deploying models to production (AWS, GCP, or Azure).
- Strong understanding of NLP, Computer Vision, or Reinforcement Learning.
- Excellent communication skills with the ability to translate technical concepts for diverse stakeholders.