Job Description
Are you ready to architect the intelligent systems of tomorrow? Nexus Horizon Technologies is seeking a visionary Senior AI/ML Engineer to lead our R&D division focused on the technological breakthroughs required for 2026 and beyond.
We are not just building software; we are defining the future of human-machine interaction. In this role, you will spearhead the development of next-generation neural architectures and deploy scalable AI solutions that redefine industry standards. Join a team that prioritizes innovation, ethical AI, and high-performance computing.
Why join us?
- Work on cutting-edge Generative AI and Autonomous Systems.
- Competitive compensation and equity packages.
- Flexible remote and hybrid work models.
- Access to state-of-the-art hardware and cloud infrastructure.
Responsibilities
- Architect & Deploy: Design, train, and deploy scalable machine learning models, with a focus on Generative AI and Predictive Analytics for the 2026 roadmap.
- Optimization: Optimize deep learning pipelines for high-performance inference in production environments, reducing latency and improving accuracy.
- Research: Conduct cutting-edge research to explore novel algorithms for autonomous decision-making systems and NLP applications.
- Collaboration: Partner with cross-functional teams (Product, Data Science, and Engineering) to integrate AI capabilities into core product infrastructure.
- Ethics & Governance: Implement robust data governance frameworks and ensure ethical AI practices across all model deployments.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related quantitative field.
- Experience: Proven experience (5+ years) in building and deploying large-scale machine learning systems in production environments.
- Technical Stack: Strong proficiency in Python, PyTorch, TensorFlow, or JAX, and experience with distributed computing (Ray, Spark).
- Cloud & Infrastructure: Deep experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to solve complex engineering challenges and translate research concepts into scalable products.
- Communication: Exceptional verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.