Job Description
Are you ready to define the future of artificial intelligence?
Nexus Innovations is seeking a visionary Senior AI/ML Engineer to lead our 2026 Roadmap initiatives. In this pivotal role, you will architect next-generation machine learning systems that push the boundaries of what's possible. We are not just building AI; we are engineering the intelligence infrastructure for the year 2026 and beyond. If you thrive in a fast-paced, high-impact environment and possess deep expertise in scalable AI systems, we want to hear from you.
Why Join Nexus?
- Work on cutting-edge Generative AI and Large Language Models (LLMs).
- Competitive compensation and equity packages.
- Flexible remote-first culture with a focus on innovation.
- Opportunity to shape the technical direction of the industry.
Responsibilities
- Architect & Deploy: Design and implement scalable machine learning models and pipelines that meet the rigorous demands of the 2026 roadmap.
- Model Optimization: Continuously optimize existing models for latency, throughput, and accuracy to ensure real-time performance.
- MLOps Leadership: Establish and maintain MLOps best practices, including CI/CD for ML, automated testing, and infrastructure as code.
- Research & Innovation: Conduct in-depth research into emerging AI techniques, specifically focusing on multimodal learning and autonomous agents.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineers to translate business requirements into technical solutions.
- Code Review & Mentorship: Provide technical leadership, mentor junior engineers, and maintain high code quality standards across the team.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in machine learning, deep learning, or artificial intelligence engineering.
- Programming: Expert-level proficiency in Python, PyTorch, or TensorFlow.
- Cloud Expertise: Strong experience deploying models on cloud platforms (AWS, GCP, or Azure) using containerization (Docker, Kubernetes).
- Mathematical Foundation: Deep understanding of linear algebra, calculus, probability, and statistics.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.