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AI Jobs at Gauss Labs
Currently hiring for 3 jobs
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AI Engineer (US)
Gauss Labs
Palo Alto, CA
At Gauss Labs we are looking for a passionate Machine Learning Engineer who will collaborate with scientists and engineers to improve manufacturing efficiency and reliability in IC manufacturing using data and artificial intelligence.
This role is responsible for implementing batch and online learning capabilities in our machine learning infrastructure. It is also responsible for capturing the lineage of our ML models as well as measuring and monitoring their performance.

Responsibilities

    • Design, build, and maintain high availability, multi-tenant training, and inference system for many different content types, such as images and other sensor data
    • Work closely with data scientists, micro-service developers, and data engineers in our Applied Research and Product Organizations to ensure efficient transfer of scalable solutions
    • Implement seamless tracking of the lineages of data sets, transformations, feature sets, and hyper-parameters used during ML model training and inference
    • Enable online learning and automated, continuous delivery of ML models
    • Implement and deploy automated auditing systems to identify bias and other potential degradations of model performance
    • Adapt and implement AI models to support real-world use-cases and satisfy production requirements as needed

Basic Qualifications

    • MS or Ph.D. in quantitative fields (CS, Statistics, Math, or Engineering)
    • 7+ years of work experience as MLE, Data Scientist, or related job function
    • Strong understanding of ML fundamentals and scaling methodologies (e.g., ability to implement an ML algorithm mathematical formulations in an efficient manner w.r.t. scalability, optimization and so on; understanding of ML loss functions, evaluation/validation methods, statistical testing and so on)
    • Strong communication skills both written and verbally
    • You are excited to learn, explore new problem areas, and apply your creativity to some of the most challenging and rewarding problems
    • Familiarity with all aspects of the model development lifecycle
    • Experience working with cloud products (AWS, GCP, or Azure)
    • Proficiency in Python, and experience in C++
    • Prior experience with MLFlow
    • Knowledge of at least one build tooling system
    • Track record of writing robust, readable, well documented, well tested, high-performance code.
    • Experience with containerization, automated eval/testing, CI/CD, MLOps, and cloud services is a plus
Full-time
Mid Level
Deep Learning
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Applied Scientist - Machine Learning & Data Science (US)
Gauss Labs
Palo Alto, CA
We are looking for a passionate and talented Machine Learning & Data Science (MLDS) Applied Scientist who will collaborate with other scientists and engineers to leverage Artificial Intelligence (AI), Machine Learning (ML), and optimization techniques to solve diverse problems in manufacturing and other industries. As a Gaussian MLDS Applied Scientist, you will design and run experiments, develop new algorithms, and find new ways of reducing cost, maximizing the performance and reliability of manufacturing systems. Besides theoretical analysis and innovation, you will work closely with seasoned scientists, engineers, and program managers to deliver your algorithms and models into real products. Your work will directly impact our customers in manufacturing lines.

You are an ideal candidate if you are enthusiastic about delivering products and solutions that are robust and dominant in the market. You thrive in ambiguous environments that require finding the best solution to open problems that have not been solved before. You leverage your exceptional technical expertise in fast-paced research and development and apply your fundamental understanding of computer science, mathematics, and statistics to create reliable, scalable high-performance products. Your strong communication skills enable you to work effectively with both business and technical partners. You have hands-on experience making the right decisions about technical methods. You strive for simplicity and elegance and demonstrate significant creativity and sound judgment backed by real data. Most of all, you are willing to take calculated risks, learn by trial and error, and grow as a team.

Responsibilities

    • Design, experiment, develop, and implement AI/ML algorithms
    • Understand business problems with insight and experience and do research to find the best solutions to the problems.
    • Develop feature engineering/extraction/selection and prediction/classification/anomaly detection algorithms especially for time-series data to solve real-world manufacturing problems
    • Use tailored supervised and unsupervised learning methods to tackle various problems occurring in manufacturing and industry in general.
    • Deliver high-quality ML solutions based on best practices for exploratory data analysis, proof-of-concept, and development of ML models.
    • Collaborate with engineering teams to design and implement software solutions for productization

Key Qualifications

    • BS/MS/PhD degree in ML/AI, Data Science, Computer Science, Electrical Engineering (EE), Statistics, Industrial Engineering, Operational Research, Mathematics, or a related field
    • Proficiency in algorithm and model development, and model validation for ML/AI applications
    • Practical and/or research experience in applying machine learning to solve real-world problems
    • Deep expertise in one or more ML/AI disciplines and scientifically versatile demonstrating scientific and industrial maturity.
    • Hands-on experience programming in Python, Matlab, R, Java, C++, or other programming languages
Full-time
Mid Level
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Applied Scientist - Machine Learning (US/KR)
Gauss Labs
Palo Alto, CA Yeoksam, Seoul /
We are looking for experienced and accomplished Applied Scientists for Machine Learning (ML). You are supposed to be strong in both practical R&D and fundamentals with deep and broad expertise in several or at least a few applied science disciplines. You should have a good understanding of the state-of-the-art ML algorithms and methods, exceptional publication records (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, ICCV, etc.), and good knowledge and experience in computer science and engineering (e.g., how to use CPUs/GPUs for efficient training and inference for diverse use cases). You should also have extensive experience and skills in collaboration with software engineering teams to enable the scaling and productization of ML algorithms.

Responsibilities

    • Develop cutting-edge Machine Learning algorithms in time-series or computer vision domain and technical areas such as online classification, regression, supervised/unsupervised learning, reinforcement learning, anomaly detection, pattern recognition, image restoration/denoising, object detection/segmentation, or hybrid ML algorithms.
    • Collaborate with other applied scientists to experiment, and develop algorithms/prototypes that advance the state-of-the-art in industrial AI.
    • Work with software engineers to provide support for scaling and productization of algorithms.
    • Work with PMs to define use cases, collect data, and benchmark the results.
    • Lead projects independently and help PMs in a dynamic environment where business, product, and technical strategies are evolving even when problems are not well understood yet.
    • Contribute to Gauss Labs's intellectual property pools through patents and technical publications.
    • Contribute to Gauss Labs's research advancement by publishing technical papers at external conferences and journals.

Key Qualifications

    • Ph.D. in Artificial Intelligence, Machine Learning, Computer Science, Electrical Engineering, Computer Vision, Statistics, or related fields.
    • 3+ years of experience doing exceptional Machine Learning research as demonstrated by both scientific publications in top venues and solutions to resolve complex business problems for potential industrial impact
    • Hands-on experience programming in Python, R, C++, Java, or other modern programming languages.
    • Experience in large-scale ML systems and related technologies, including commercial cloud stacks, resource provisioning/orchestration, and scaling methodologies (e.g., distributed optimization).
Full-time
Senior
Deep Learning