Job Description
Are you ready to architect the next generation of intelligent systems? Nexus Horizon Solutions is seeking a visionary Senior AI/ML Engineer to join our elite engineering team. In this pivotal role, you will define the technical roadmap for 2026, developing scalable machine learning models that drive our core product innovation.
We are not just looking for a coder; we are looking for a technical leader who thrives on solving complex problems and pushing the boundaries of what's possible with Artificial Intelligence.
Why Join Us?
- Work with cutting-edge technology stack including Python, TensorFlow, and cloud-native architectures.
- Competitive equity package and comprehensive benefits plan.
- Flexible remote and hybrid work arrangements.
- Opportunity to mentor junior engineers and shape the culture of technical excellence.
Responsibilities
- Model Development & Deployment: Design, train, and deploy robust machine learning and deep learning models to production environments using MLOps best practices.
- Architecture Strategy: Lead the architectural design of scalable AI systems that align with our 2026 product vision and long-term business goals.
- Performance Optimization: Continuously monitor, evaluate, and optimize model performance to ensure high accuracy and low latency.
- Data Pipeline Management: Collaborate with data engineers to build efficient data pipelines and ensure high-quality data ingestion for training.
- Research & Innovation: Stay abreast of the latest research in AI/ML and experiment with novel algorithms to improve our competitive edge.
- Technical Leadership: Provide technical guidance to the engineering team, conducting code reviews and architectural reviews.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, or a related field. PhD preferred.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Technical Skills: Proficiency in Python, PyTorch or TensorFlow. Experience with cloud platforms (AWS, GCP, or Azure) is essential.
- MLOps: Strong understanding of MLOps tools (Docker, Kubernetes, MLflow) and CI/CD pipelines.
- Problem Solving: Demonstrated ability to solve complex, ambiguous problems with creative engineering solutions.
- Communication: Excellent verbal and written communication skills; ability to translate technical concepts to non-technical stakeholders.