We are seeking highly motivated AI Scientists to serve as technical leaders who shape the long-term direction of multiple initiatives. In this role, you will solve complex and novel ML challenges, introduce transformative approaches, and ensure that innovation is applied at scale across projects. You will mentor junior/senior peers, influencing both engineering and product strategy. Their scope extends from direct execution to setting vision and ensuring sustainable growth in technical capability. 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.
We are seeking highly motivated AI Scientists to serve as technical leaders who shape the long-term direction of multiple initiatives. In this role, you will solve complex and novel ML challenges, introduce transformative approaches, and ensure that innovation is applied at scale across projects. You will mentor junior/senior peers, influencing both engineering and product strategy. Their scope extends from direct execution to setting vision and ensuring sustainable growth in technical capability. 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. or Master’s degree 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.
Ces cookies sont nécessaires au fonctionnement du site web et ne peuvent pas être désactivés dans nos systèmes. Vous pouvez configurer votre navigateur pour qu'il bloque ces cookies, mais certaines parties du site risquent alors de ne pas fonctionner.
Sécurité
Expérience utilisateur
Cookies ciblés
Ces cookies sont placés par nos partenaires publicitaires via notre site web. Ils peuvent être utilisés par ces entreprises pour créer un profil de vos intérêts et vous montrer des publicités pertinentes ailleurs.
Google Analytics
Google Ads
Nous utilisons des cookies
🍪
Notre site web utilise des cookies et des technologies similaires pour personnaliser le contenu, optimiser l'expérience de l'utilisateur, individualiser et évaluer la publicité. En cliquant sur OK ou en activant une option dans les paramètres des cookies, vous acceptez cela.
Les meilleurs emplois à distance par courriel
Rejoins 5'000+ personnes qui reçoivent des alertes hebdomadaires avec des emplois à distance!