Machine Learning (ML) Engineer to create natural language understanding modules and/or artificial intelligence products. The Candidate should be able to create machine learning pipelines that include data cleaning, pre-processing, training, and multi-model deployments targeting high-performance servers to low-power devices.
- Study and transform data science prototypes.
- Design machine learning systems.
- Research and implement appropriate ML algorithms and tools.
- Develop ML applications according to requirements.
- Select appropriate datasets and data representation methods.
- Run ML tests and experiments.
- Perform statistical analysis and fine-tuning using test results.
- Train and re-train systems when necessary.
- Extend existing ML libraries and frameworks.
- Keep abreast of developments in the field.
- Various assigned tasks/projects.
- 3+ years of experience.
- Experience using Kubernetes for highly scalable ML applications.
- Experience building ML applications using Tensorflow Lite on iOS/Android devices.
- Experience and strong knowledge in frameworks such Pytorch and/or Tensorflow.
- Strong general software development skills (source code management, debugging, testing, deployment, etc).
- Experience in state-of-the-art NLP technologies such as Glove, BERT, and ALBERT.
- Thorough understanding of text preprocessing and normalization techniques (tokenization, lemmatization, stemming, POS tagging, and parsing).
- Working experience in Software Development Lifecycle, Agile Methodologies, and Continuous Integration.
- Ability to write robust code in Python, Go, and C++.
- Excellent communication skills.
- Ability to work closely in a team.
- Outstanding analytical and problem-solving skills.