Job Description
Join NexGen Systems as a Senior Machine Learning Engineer and help define the architecture of the 2026 platform. We are building the next generation of autonomous decision-making software, and we need a visionary engineer to lead our core algorithmic teams. This is a unique opportunity to work on high-impact projects that will shape the future of enterprise AI.
We offer a competitive compensation package, comprehensive health benefits, and a dynamic environment where innovation is not just encouraged, it's required.
Key Responsibilities:
Responsibilities
- Design and implement scalable machine learning models and infrastructure for the 2026 platform, ensuring high accuracy and low latency in production environments.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate business requirements into technical solutions.
- Optimize existing models for performance, efficiency, and cost-effectiveness using techniques such as quantization, pruning, and model distillation.
- Build and maintain robust MLOps pipelines using tools like Kubernetes, TensorFlow Extended (TFX), and Airflow to streamline model deployment and monitoring.
- Conduct rigorous A/B testing and statistical analysis to validate model performance and drive continuous improvement.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and knowledge sharing within the team.
- Stay abreast of the latest advancements in AI research (e.g., Transformers, GNNs) and evaluate their applicability to our product roadmap.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience.
- Minimum of 5+ years of professional experience in building, deploying, and maintaining production-grade machine learning models.
- Proficiency in programming languages such as Python, with deep expertise in frameworks like PyTorch, TensorFlow, or JAX.
- Strong understanding of deep learning architectures, natural language processing (NLP), and computer vision.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of working with large-scale datasets and experience in distributed computing environments.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, agile development environment.