Senior Unstructured Data Scientist

Position Overview

Our unstructured data science and machine learning team in EMEA is seeking a senior machine learning engineer with a solid background and focus on unstructured data applied science in Computer Vision (CV) or Natural Language Processing (NLP), either text or speech. The team needs someone who is a skilled software engineer and proficient in ML libraries, system design, and pipelines. In this role, you will be building state-of-the-art models for our products, using test-driven development, and working with the software engineering team to deploy and maintain the models in production.

Job Duties/Responsibilities

• Design, train and deliver machine learning solutions to a wide range of datasets: from small datasets to big data, both unlabeled and labeled.
• Collaborate with the development team and ML engineers to implement, test, and validate new algorithms and integrate the algorithms with the existing front-end and back-end systems.
• Build state-of-the-art models for various modeling tasks (e.g., speech recognition, optical character recognition, text-to-speech, facial recognition, time series forecasting, … etc.)
• Optimize and automate model training and testing, experimentation tracking, development, and production.
• Skilled in breaking down problems, documenting problem statements and estimating efforts.
• Mentor junior engineers, perform code reviews and document design decisions.
• Create web services/APIs for serving ML/AI model results.
• Familiar with MLOps Tools (e.g., MLFlow, Kubeflow, … etc.).
• Familiar with unsupervised, semi-supervised, and self-supervised techniques.
  

Minimum Qualifications

• PhD or MS in Computer Science, Electrical Engineering, or similar field
• 5+ years of experience with one modern language such as C++, Python including object-oriented design.
• 5+ years of experience with machine learning tools and deep learning algorithms and techniques, including but not limited to:
• PyTorch, TensorFlow, Keras, Kaldi
• CNN, LSTM, RNN
• Scikit-learn, pandas, NumPy
• Optimization techniques and fine-tuning models
• State-of-the-art Machine Learning algorithms and techniques (e.g., Transformers).
• 3+ years of experience contributing to the architecture and design (architecture, design patterns, reliability, and scaling) of new and current systems.
• Experience with MLOps and other production level implementation frameworks and pipelines
• Experience with Docker, Kubernetes, and cloud platforms
• Able to work independently on problems and in highly collaborative team environments.