We are looking for a Machine Learning/NLP Engineer to join our team in London.
As a Machine Learning/NLP Engineer you will be responsible for both
advancing the implementation efforts of our Machine Learning and NLP
pipelines for large-scale deployment and training, as well as conducting
research experiments that advance our capabilities and understanding.
You will be involved from concept, all the way through deployment
working closely with the team and taking part in the complete project
life cycle, where you will have significant influence. Your work will
lie in proposing and discovering novel methods that work well in
practice and deploying them in the real world.
The role will entail designing and implementing a scalable workflow
infrastructure, which will orchestrate the training and deployment of
the distributed ML system - involving identifying bottlenecks and
elaborating solutions. You will design and execute state-of-the-art
experiments - including fast system prototyping - that have the
potential to enhance or transform our overall system performance. Also,
you will work alongside scientists and research engineers to contribute
to technical blog posts, research papers, and open source
implementations to further explore and research novel methods.
Basic skills:
- Bachelor's Degree in Computer Science or related field
- Proficient in Unix environments, Python and Machine Learning libraries such as Tensorflow, Pytorch, Sklearn, pandas, NumPy
- Knowledge of software engineering practices and best practices for the full engineering (CI/CD, Docker, AWS etc.) life-cycle
- Understanding of design for scalability, performance and reliability of large-scale distributed ML systems
- Ability to produce well documented code that is fault-tolerant, efficient, and maintainable
Preferred skills (nice-to-haves):
- Master's Degree/PhD in Machine Learning, Computer Science, or related field
- Proficiency in other modern programming languages such as C++, Java, Scala
- 1-2+ years academic and/or industry experience working on Dialogue - Systems, NLP systems and/or large-scale Machine Learning
- Has produced demonstrable work in building real-world deployed machine learning/NLP systems
- Competent with large-scale data-serving and compute libraries and software, such as Hadoop, Spark, Apache Mesos, etc.
