Job Description
We are looking for a visionary Senior AI Engineer to join Nexus Future Systems. We are pioneering the next generation of intelligent systems, leveraging cutting-edge Large Language Models (LLMs) and generative AI to solve complex real-world problems. If you are passionate about building scalable, robust AI infrastructure and want to shape the future of technology, this is the opportunity for you.
Why You'll Love It Here:
- Impactful Work: Develop AI solutions that drive tangible business value.
- Innovation First: Work with the latest tools in MLOps and Deep Learning.
- Competitive Package: Comprehensive benefits, equity, and a dynamic work environment.
Key Responsibilities:
- Architect, design, and deploy scalable machine learning models and AI applications.
- Collaborate closely with data scientists and backend engineers to optimize model performance and latency.
- Design and implement MLOps pipelines for automated training, evaluation, and deployment.
- Stay at the forefront of AI research and translate theoretical advancements into practical engineering solutions.
- Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
- Ensure data privacy, security, and compliance in all AI implementations.
Qualifications:
- Master’s or PhD in Computer Science, Statistics, Mathematics, or a related technical field.
- 5+ years of professional experience in Machine Learning and Software Engineering.
- Proficiency in Python, PyTorch, or TensorFlow.
- Strong foundation in Deep Learning architectures (Transformers, CNNs, RNNs).
- Experience with cloud platforms (AWS, GCP) and containerization technologies (Docker, Kubernetes).
- Proven track record of shipping production-grade ML systems.
Responsibilities
- Architect, design, and deploy scalable machine learning models and AI applications.
- Collaborate closely with data scientists and backend engineers to optimize model performance and latency.
- Design and implement MLOps pipelines for automated training, evaluation, and deployment.
- Stay at the forefront of AI research and translate theoretical advancements into practical engineering solutions.
- Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
- Ensure data privacy, security, and compliance in all AI implementations.
Qualifications
- Master’s or PhD in Computer Science, Statistics, Mathematics, or a related technical field.
- 5+ years of professional experience in Machine Learning and Software Engineering.
- Proficiency in Python, PyTorch, or TensorFlow.
- Strong foundation in Deep Learning architectures (Transformers, CNNs, RNNs).
- Experience with cloud platforms (AWS, GCP) and containerization technologies (Docker, Kubernetes).
- Proven track record of shipping production-grade ML systems.