AI Scientist - Machine Learning (KR/US)

Gauss Labs; Palo Alto (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

Gauss Labs is seeking an AI Scientist with a focus on Machine Learning to drive transformative time-series modeling in manufacturing. You will design Transformer-based solutions, own the ML lifecycle from data exploration to deployment, and collaborate with cross-functional teams to deliver scalable AI software.

The role emphasizes production-ready ML, performance optimization, and contributing to IP through publications and patents. A PhD and strong publication record are highly valued.

Qualifications

• Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.
• 3+ years of hands-on experience in deep learning, with a strong focus on sequence modeling and time-series forecasting.
• In-depth expertise in Transformer architectures and their applications beyond natural language processing.
• Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Solid mathematical foundation in statistics, optimization, and signal processing.
• Familiarity with hybrid modeling approaches that combine deep learning and traditional statistical methods.
• Experience working with noisy, sparse, or irregularly sampled time-series data.
• Strong publication track record in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR).
• Practical experience deploying ML models in production environments, with knowledge of MLOps best practices.
• Nice to have Familiar with state-of-the-art neural networks architecture. Preferably had experience in innovation in new architecture such as transformer based models

Responsibilities

• Design and implement Transformer-based architectures for time-series prediction and sequence modeling, across both univariate and multivariate data
• Drive the full machine learning lifecycle—from exploratory data analysis to model deployment, monitoring, and continuous improvement
• Conduct rigorous benchmarking, ablation studies, and performance optimization to ensure robustness and efficiency
• Collaborate closely with data scientists, engineers, and product managers to translate complex business requirements into scalable technical solutions
• Partner with software engineers to scale and productize ML algorithms within manufacturing AI software products
• Contribute to Gauss Labs' intellectual property portfolio through patents and high-impact technical publications
• Mentor junior team members and play an active role in shaping the team's AI roadmap and long-term strategy

Skills

Transformer architectures

Sequence modeling

Time-series forecasting

Python

PyTorch

TensorFlow

JAX

Statistical methods

ML deployment

ML lifecycle

Education

Ph.D. in Computer Science or ML

Tools

PyTorch

TensorFlow

JAX

Job description

We are seeking a highly motivated AI Scientist specializing in Machine Learning to join our growing AI R&D team. In this role, you will be at the forefront of developing and deploying cutting-edge deep learning models to solve real-world temporal modeling challenges in manufacturing. We're looking for a candidate with strong practical R&D experience, grounded in solid theoretical fundamentals, and deep expertise in AI disciplines. The ideal candidate will have a deep understanding of state-of-the-art machine learning algorithms and techniques, a track record of impactful publications in top-tier conferences such as NeurIPS, ICML, ICLR, KDD, CVPR, or ICCV, and a solid background in computer science and engineering. Experience collaborating with software engineering teams to scale and productize ML solutions is a strong plus. This is a high-impact role that combines foundational research, system-level design, and hands-on implementation. You'll work closely with cross-functional teams to develop innovative solutions that guide strategic decisions and deliver tangible business value.

Responsibilities

• Design and implement Transformer-based architectures for time-series prediction and sequence modeling, across both univariate and multivariate data
• Drive the full machine learning lifecycle—from exploratory data analysis to model deployment, monitoring, and continuous improvement
• Conduct rigorous benchmarking, ablation studies, and performance optimization to ensure robustness and efficiency
• Collaborate closely with data scientists, engineers, and product managers to translate complex business requirements into scalable technical solutions
• Partner with software engineers to scale and productize ML algorithms within manufacturing AI software products
• Contribute to Gauss Labs' intellectual property portfolio through patents and high-impact technical publications
• Mentor junior team members and play an active role in shaping the team's AI roadmap and long-term strategy

Key Qualifications

• Ph.D. in Computer Science, Machine Learning, Statistics, or a related field
• 3+ years of hands-on experience in deep learning, with a strong focus on sequence modeling and time-series forecasting
• In-depth expertise in Transformer architectures and their applications beyond natural language processing
• Proficiency in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX
• Solid mathematical foundation in statistics, optimization, and signal processing
• Familiarity with hybrid modeling approaches that combine deep learning and traditional statistical methods
• Experience working with noisy, sparse, or irregularly sampled time-series data
• Strong publication track record in top-tier ML/AI conferences (e.g., NeurIPS, ICML, ICLR)
• Practical experience deploying ML models in production environments, with knowledge of MLOps best practices
• [Nice to have] Familiar with state-of-the-art neural networks architecture. Preferably had experience in innovation in new architecture such as transformer based models