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.

What you will do

• Provide scientific 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 such as 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 scientists and software 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 effective, highly technical and complex solutions and architectures to audiences with limited or no experience in machine learning solutions.

Your minimum qualifications are

• Advanced degree (Ph.D. preferred, Masters accepted) 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.
• 7+ years of industry experience in designing and implementing machine learning models at scale, with a track record of deploying them in large-scale production environments.
• Experience with any of the following: SotA attention models, large language models, conversational AI, virtual assistants, document understanding, spoken language understanding, information retrieval, question answering, or related fields.
• Experience in LLM reasoning, ACT, and React methods.
• Experience in developing and debugging in Python, C, C++ or C#.
• Fluent in building models with Python and state-of-the-art machine learning libraries (e.g. PyTorch, TensorFlow, MxNet).
• Experience or willingness to learn and work in Agile and iterative development and DevOps processes.
• Ability to work with minimal supervision, keeping a strong alignment with your technical peers, non-technical partners, and the overall company objective.
• You enjoy and thrive in a fast-working collaborative environment.

Nice to haves

• Experience in designing, building, and deploying end-to-end ML pipelines using deep learning frameworks such as Scikit-learn, PyTorch, and TensorFlow.
• Familiarity with MLOps and AutoML platforms, including Kubeflow, MLflow, Kubernetes, and Docker.
• Experience with cloud infrastructure orchestration using scripting tools.

Preferred qualifications

• A deep experience and understanding in statistics, mathematical models, Multivariate and DL algorithms.
• Experience in machine translation.
• Experience in document understanding.
• Reinforcement learning with human feedback (RLHF).
• Multimodal deep learning models.
• An impressive Google Scholar portfolio.
• A strong track record in starting or contributing to open-source ML platforms, tools, and projects.