Job Description
Are you ready to architect the future of intelligent systems? Nexus AI Labs is at the forefront of Generative AI, deploying transformative models that redefine human-computer interaction. We are seeking a visionary Senior AI/ML Engineer to join our elite engineering team and lead the next generation of neural network architectures.
In this pivotal role, you will bridge the gap between cutting-edge research and production-grade scalability. You will own the end-to-end lifecycle of large language models (LLMs), ensuring they are not only technically superior but also efficient, secure, and compliant with global standards.
Join us in shaping the AI landscape of 2026 and beyond. If you thrive in a fast-paced, innovative environment and are passionate about pushing the boundaries of what's possible with artificial intelligence, we want to hear from you.
Responsibilities
- Model Architecture & Development: Design, train, and fine-tune state-of-the-art deep learning models, with a focus on Generative AI and Large Language Models (LLMs).
- Production Deployment: Oversee the deployment of models into high-availability cloud environments (AWS/GCP), ensuring seamless integration and monitoring.
- Performance Optimization: Optimize model inference latency and throughput, implementing techniques such as quantization, pruning, and distillation.
- MLOps & Infrastructure: Build and maintain robust MLOps pipelines to automate model training, validation, and deployment processes using tools like Docker, Kubernetes, and MLflow.
- R&D Collaboration: Partner with research scientists to translate theoretical breakthroughs into practical, scalable applications.
- Code Review & Mentorship: Provide technical leadership, conduct rigorous code reviews, and mentor junior engineers and data scientists on best practices in AI engineering.
- Compliance & Ethics: Ensure all AI systems adhere to ethical guidelines, privacy regulations (GDPR/CCPA), and safety protocols.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, or a related field (or equivalent practical experience).
- Core Skills: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Strong understanding of neural network theory and optimization algorithms.
- Experience: 5+ years of professional experience in machine learning engineering, with at least 2 years specifically in Generative AI or NLP.
- Cloud Proficiency: Extensive experience deploying models on major cloud providers (AWS, Azure, or GCP) and familiarity with serverless architectures.
- Tools & Frameworks: Proficiency in MLOps tools (Docker, Kubernetes, CI/CD), version control (Git), and data visualization libraries (TensorBoard, Weights & Biases).
- Problem Solving: Exceptional analytical skills with a proven track record of solving complex, ambiguous problems in high-stakes environments.
- Communication: Excellent written and verbal communication skills, capable of articulating complex technical concepts to diverse stakeholders.