Job Description
We are on the forefront of technological evolution, building the intelligent systems that will define the year 2026 and beyond. As a Senior AI & Machine Learning Engineer at Nexus Innovations, you won't just maintain the status quo; you will architect the future. We are seeking a visionary technologist to lead our cutting-edge research in Generative AI, Large Language Models (LLMs), and autonomous decision-making systems.
In this pivotal role, you will bridge the gap between theoretical research and production-scale deployment. You will work with a world-class team of data scientists and engineers to solve complex problems that have no obvious answers. If you are passionate about the potential of artificial intelligence and want to leave a lasting legacy in the tech landscape, we want to hear from you.
Why Join Us?
- Future-Ready Tech Stack: Work with the latest in PyTorch, TensorFlow, and cloud-native AI infrastructure.
- Impact: Your work will directly influence the next generation of human-computer interaction.
- Equity: Competitive stock options and performance bonuses.
- Flexibility: Hybrid work model supporting top-tier talent regardless of location.
Responsibilities
- Architect and deploy scalable machine learning models, focusing on Generative AI and NLP for the 2026 roadmap.
- Lead the end-to-end machine learning lifecycle from data ingestion and preprocessing to model training, evaluation, and deployment.
- Collaborate with product managers and engineers to translate business requirements into technical AI solutions.
- Optimize existing models for latency, throughput, and cost efficiency in high-traffic environments.
- Conduct cutting-edge research to stay ahead of industry trends in deep learning and neural networks.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Ensure ethical AI practices and data privacy compliance in all algorithmic implementations.
Qualifications
- Master’s degree or PhD in Computer Science, Mathematics, Statistics, or a related technical field (or equivalent practical experience).
- 5+ years of professional experience in Machine Learning, AI, or Data Science.
- Strong proficiency in Python and deep understanding of major ML frameworks (PyTorch, TensorFlow, JAX).
- Proven experience with training and fine-tuning Large Language Models (LLMs) or similar generative models.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to work in a fast-paced, agile environment.
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.