Job Description
We are seeking a visionary Senior AI Engineer to lead the next generation of intelligent systems. NeuroLogic Solutions is pioneering the development of scalable, safe, and efficient Large Language Models (LLMs) that redefine human-machine interaction.
In this pivotal role, you will architect and implement deep learning architectures that solve complex real-world problems. You will work in a collaborative, high-performance environment alongside top-tier researchers and engineers to push the boundaries of Natural Language Processing (NLP) and Generative AI.
What you will do:
- Design, train, and fine-tune state-of-the-art deep learning models using PyTorch and TensorFlow.
- Optimize model inference latency and throughput for production environments.
- Conduct novel research to improve model accuracy, generalization, and robustness.
- Implement MLOps best practices for model versioning, monitoring, and automated retraining pipelines.
- Collaborate with cross-functional teams to integrate AI models into consumer-facing products.
Qualifications:
- PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Proven experience building and deploying production-grade NLP models (BERT, GPT, etc.).
- Strong proficiency in Python, C++, and SQL.
- Deep understanding of machine learning fundamentals, optimization theory, and distributed systems.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
Ready to shape the intelligence of tomorrow? Apply today.
Responsibilities
- Design, train, and fine-tune state-of-the-art deep learning models using PyTorch and TensorFlow.
- Optimize model inference latency and throughput for production environments.
- Conduct novel research to improve model accuracy, generalization, and robustness.
- Implement MLOps best practices for model versioning, monitoring, and automated retraining pipelines.
- Collaborate with cross-functional teams to integrate AI models into consumer-facing products.
- Present technical findings to stakeholders and contribute to technical documentation.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Proven experience building and deploying production-grade NLP models (BERT, GPT, etc.).
- Strong proficiency in Python, C++, and SQL.
- Deep understanding of machine learning fundamentals, optimization theory, and distributed systems.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.