Job Description
Are you ready to define the next era of artificial intelligence? Nexus Horizon Technologies is seeking a visionary Senior AI Engineer to join our elite '2026' initiative. We are building the foundational models that will power enterprise solutions for the next decade. If you thrive in a fast-paced, innovative environment and want to push the boundaries of what's possible with Generative AI and Large Language Models (LLMs), this is your opportunity.
Why Join Us?
- Work on groundbreaking projects that will shape the future of technology.
- Competitive compensation package with equity options.
- Top-tier benefits and flexible remote-first culture.
- Access to state-of-the-art compute resources and research libraries.
Role Overview:
You will be responsible for designing, training, and deploying scalable AI models. You will work closely with cross-functional teams of data scientists, engineers, and product managers to deliver high-impact solutions that solve complex real-world problems.
Responsibilities
- Model Development: Design and implement state-of-the-art machine learning and deep learning algorithms to drive product innovation.
- Optimization: Optimize model inference latency and accuracy for production environments, ensuring scalability and efficiency.
- Research: Stay ahead of the curve by researching emerging AI trends and methodologies, specifically focusing on the roadmap towards 2026.
- Collaboration: Partner with engineering and product teams to integrate AI models into seamless user experiences.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Deployment: Manage the full ML lifecycle, from data ingestion to model serving and monitoring.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in machine learning or AI engineering.
- Core Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Domain Knowledge: Strong understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Tools: Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (Kubernetes, MLflow, Docker).
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.