Established expertise and genuine passion for natural language processing (NLP), machine learning, deep learning, and large language models. Experience crafting machine learning models in cloud environments like AWS or GCP, with specific knowledge of Sagemaker being a plus.

Hands-on experience in one or more of the following areas: Machine Learning, Deep Learning, Recommender Systems, Data Mining, Natural Language Processing, or Computer Vision.

Earned graduate degree (Ph. D. or M.Sc. + 2 years relevant industry experience) in a highly quantitative discipline (e.g., machine learning, statistics, computer science, applied mathematics, theoretical physics, physical chemistry, econometrics, bioinformatics.

We are hiring a Machine Learning Engineer to be involved in designing and building large-scale applications and systems to acquire, process, and store multi-terabytes of YouTube, TikTok, Facebook and other social media data.

Development efforts may include all areas of computer sciences, including big data analytics and search engine technology, natural language processing, distributive computing, large scale system design, user interface design, computer graphics, and even virtual reality.

4+ years experience as an Machine Learning Engineer, Applied Scientist, or similar role. As a Senior Machine Learning Engineer, you will be responsible for developing ML solutions to increase the safety, efficiency and sustainability of the physical operations.

Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems, backend, large-scale systems, data science, full-stack.

Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.

8+ years of professional data engineering or software engineering experience, with a focus on heterogeneous, large-scale data processing for machine learning pipelines.

Experience in Natural language processing (NLP), Prompt engineering, Embedding, Vector DB. They will use relevant statistical techniques, machine learning models and artificial intelligence algorithms to analyze data, design data models and derive insights to influence actions that maximize business value and effectiveness for the commercial technology segments.

Knowledge and/or familiarity of the midstream services industry and data generated in support of business activities related to the gathering, compressing, treating, processing, and selling natural gas, NGLs and NGL products, and crude oil will be strongly preferred.

Deep Learning Ninja: Proven experience in designing and implementing machine learning solutions utilizing GCP and various algorithms (e.g., TensorFlow, PyTorch). As a Machine Learning Engineer specializing in Google Cloud Platform (GCP), youll lead the charge in developing and deploying cutting-edge solutions that extract valuable insights and drive tangible business outcomes.

Proficiency and experience in applied statistics and machine learning fields e.g. Experimentation and Causal Analysis, Recommendations, Fraud & Anomaly Detection, Natural Language, Computer Vision.

The URBS-lab focuses on the development and application of machine learning, artificial intelligence, and statistical methodologies targeting a variety of domains and data types within biomedical research.

In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques.