Job Description
NeuralPath Systems is at the forefront of the Generative AI revolution, building large-scale models that redefine industry standards. We are seeking a visionary Senior Machine Learning Engineer to join our core research and deployment team in San Francisco. You will play a pivotal role in designing, training, and optimizing state-of-the-art transformer architectures to solve complex, real-world challenges.
If you are passionate about pushing the boundaries of AI, thrive in a collaborative high-growth environment, and are eager to work with massive datasets, we want to hear from you.
Responsibilities
- Architect and train large-scale generative models using PyTorch or TensorFlow.
- Optimize model inference pipelines for high-throughput, low-latency production environments.
- Collaborate with data scientists to curate high-quality training datasets and implement advanced data augmentation techniques.
- Develop robust evaluation frameworks to benchmark model performance and identify edge cases.
- Mentor junior engineers and lead internal R&D initiatives for model efficiency.
- Conduct cutting-edge research to stay ahead of industry trends and apply findings to product development.
- Deploy scalable ML services on distributed cloud infrastructure (AWS/GCP/Azure).
Qualifications
- M.S. or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in machine learning, with a focus on Deep Learning and LLMs.
- Proven expertise in Python and deep learning frameworks like PyTorch or JAX.
- Deep understanding of transformer architectures, attention mechanisms, and fine-tuning techniques (RLHF, LoRA).
- Experience with distributed training frameworks such as DeepSpeed or Megatron-LM.
- Strong background in data structures, algorithms, and software engineering best practices.
- Ability to communicate complex technical concepts to non-technical stakeholders.