Come join a team of industry and science leaders to achieve a vision of empowering innovation through state-of-the-art artificial intelligence and machine learning. We are addressing exciting challenges for our customers, at the intersection of AI/ML and cutting-edge cloud infrastructure, with NLP being a core area of what we do and what we offer our customers.
Provide machine learning methodology leadership.
Use AI/ML to solve NLP tasks and hard challenges, primarily for internal projects (i.e. for our product offering) and also for external projects (e.g. for customer projects).
Build state-of-the-art models for cognitive services using various open source and machine learning principles and techniques (including but not limited to Classical Machine Learning, like logistic regression, SVM, NN, Clustering, and Deep Learning, including CNN, RNN, Transformer, Seq2Seq, BERT).
Brainstorm and design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
Collaborate with fellow data scientists and SW engineers to build out various parts of our AI/ML infrastructure, services, and solutions, and effectively communicate the solutions to address external and internal shareholder's product challenges by presenting to highly technical audiences.
Present effectively, highly technical, and complex solutions and architectures to audiences with limited or no experience in machine learning solutions.
You have deep knowledge and work experience in mathematical and Statistical models like State Estimation techniques, statistical risk analysis using Monte Carlo Simulation, stochastic optimization, and time-series forecasting.
You know how to leverage state-of-the-art cloud technology – AWS, GCP, Azure, Heroku, or similar technology.
You are fluent in building models with Python and state-of-the-art machine learning libraries (e.g. Pytorch, Tensorflow, MxNet), and can leverage Hadoop, HBase, Spark, etc.
You have deep knowledge and experience in mathematical and statistical models, including state estimation techniques, statistical risk analysis, stochastic optimization, and/or time-series forecasting.
Capable of quickly becoming familiar with new approaches to or platforms for Machine Learning and applying these to real-world problems and platforms, in particular in the NLP space.
You have been exploring or working on some of the latest advancements in NLP using deep learning such as Deep Semantic Search, Deep Language Models (e.g. GPT-2 and GPT-3), conversational & cognitive communication technology such as chatbots and virtual assistants.
You are able to work with minimal supervision, keeping a strong alignment with your technical peers, non-technical partners, and the overall company objective.
You are able to positively influence and lead other data scientists (within your team, and with other scientists in the community) on science projects and initiatives.
You enjoy and thrive in a fast-working collaborative environment
Advanced degree (Ph.D. preferred) in computer science, Physics, Electrical Engineering, Statistics, or Mathematics, preferably with specialization in Artificial intelligence, Machine Learning, Speech Recognition, Natural Language Processing, Operations Research, or a related field.
10+ years of experience in designing and implementing machine learning models at scale, and a track record of deploying them in large-scale production environments.
Experience using ML and DL languages using Python and Java, to manipulate data and draw insights.
Practical experience and deep knowledge in algorithms for Anomaly detection, NLP, NLU, sentiment analysis, Text to Speech, Machine Translation, Recommender Systems, Reinforcement Learning, and other AI approaches.
Deep understanding of data structures, algorithms, and excellent problem-solving skills.
Experience or willingness to learn and work in Agile and iterative development and DevOps processes.
A deep experience and understanding of Statistics, Mathematical models, Multivariate and DL algorithms.
Experience with Cloud Native Frameworks tools and products
An Impressive portfolio on Kaggle Profile.
An impressive Google Scholar portfolio.
A strong track record in starting or contributing to open source ML platforms, tools, and projects.
Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies.
aiXplain
Los Gatos California
United States
Scientific Research
(No Timezone Provided)
Come join a team of industry and science leaders to achieve a vision of empowering innovation through state-of-the-art artificial intelligence and machine learning. We are addressing exciting challenges for our customers, at the intersection of AI/ML and cutting-edge cloud infrastructure, with NLP being a core area of what we do and what we offer our customers.
Provide machine learning methodology leadership.
Use AI/ML to solve NLP tasks and hard challenges, primarily for internal projects (i.e. for our product offering) and also for external projects (e.g. for customer projects).
Build state-of-the-art models for cognitive services using various open source and machine learning principles and techniques (including but not limited to Classical Machine Learning, like logistic regression, SVM, NN, Clustering, and Deep Learning, including CNN, RNN, Transformer, Seq2Seq, BERT).
Brainstorm and design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
Collaborate with fellow data scientists and SW engineers to build out various parts of our AI/ML infrastructure, services, and solutions, and effectively communicate the solutions to address external and internal shareholder's product challenges by presenting to highly technical audiences.
Present effectively, highly technical, and complex solutions and architectures to audiences with limited or no experience in machine learning solutions.
You have deep knowledge and work experience in mathematical and Statistical models like State Estimation techniques, statistical risk analysis using Monte Carlo Simulation, stochastic optimization, and time-series forecasting.
You know how to leverage state-of-the-art cloud technology – AWS, GCP, Azure, Heroku, or similar technology.
You are fluent in building models with Python and state-of-the-art machine learning libraries (e.g. Pytorch, Tensorflow, MxNet), and can leverage Hadoop, HBase, Spark, etc.
You have deep knowledge and experience in mathematical and statistical models, including state estimation techniques, statistical risk analysis, stochastic optimization, and/or time-series forecasting.
Capable of quickly becoming familiar with new approaches to or platforms for Machine Learning and applying these to real-world problems and platforms, in particular in the NLP space.
You have been exploring or working on some of the latest advancements in NLP using deep learning such as Deep Semantic Search, Deep Language Models (e.g. GPT-2 and GPT-3), conversational & cognitive communication technology such as chatbots and virtual assistants.
You are able to work with minimal supervision, keeping a strong alignment with your technical peers, non-technical partners, and the overall company objective.
You are able to positively influence and lead other data scientists (within your team, and with other scientists in the community) on science projects and initiatives.
You enjoy and thrive in a fast-working collaborative environment
Advanced degree (Ph.D. preferred) in computer science, Physics, Electrical Engineering, Statistics, or Mathematics, preferably with specialization in Artificial intelligence, Machine Learning, Speech Recognition, Natural Language Processing, Operations Research, or a related field.
10+ years of experience in designing and implementing machine learning models at scale, and a track record of deploying them in large-scale production environments.
Experience using ML and DL languages using Python and Java, to manipulate data and draw insights.
Practical experience and deep knowledge in algorithms for Anomaly detection, NLP, NLU, sentiment analysis, Text to Speech, Machine Translation, Recommender Systems, Reinforcement Learning, and other AI approaches.
Deep understanding of data structures, algorithms, and excellent problem-solving skills.
Experience or willingness to learn and work in Agile and iterative development and DevOps processes.
A deep experience and understanding of Statistics, Mathematical models, Multivariate and DL algorithms.
Experience with Cloud Native Frameworks tools and products
An Impressive portfolio on Kaggle Profile.
An impressive Google Scholar portfolio.
A strong track record in starting or contributing to open source ML platforms, tools, and projects.
Hands-on experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies.