Thomson Reuters is offering internship opportunity as Software Engineer – ML – Intern
Software Engineer – ML – Intern
JOB INFORMATION :
Job Function: Graduates/Interns
About The Role
In this opportunity as an Intern with a specialization in Machine Learning, you will:
Develop and Deliver: Applying modern development practices, you will be involved in the entire software development lifecycle, building, testing, and delivering high-quality solutions.
Solve Complex Problems: You will create large scale data processing pipelines to help researchers build and train novel machine learning algorithms. You will develop high performing scalable systems in the context of large online delivery environments.
Be a Team Player: Working in a diverse and collaborative team-oriented environment, you will share information, value diverse ideas, partner with cross-functional and remote teams.
Be Innovative: You are empowered to try new approaches and learn new technologies. You will contribute innovative ideas, create solutions, and be accountable for end-to-end deliveries.
Be an Effective Communicator: Through active engagement and communication with cross-functional partners and team members, you will effectively articulate ideas and collaborate on technical developments.
Your short-term tasks will be focused on:
Familiarizing and adopting work methodology aligning with the existing engineering organization.
Contributing to the delivery for key initiatives already in-flight within the labs engineering organization.
You’re a fit for the role of Machine Learning Engineer – Intern, if you:
Can “think in code” and have a deep understanding of the Python software development stacks and ecosystems
Have a fundamental understanding of the Software development Lifecycle and familiar with common tools used for the same
Can understand, apply, integrate, and deploy Machine Learning capabilities and techniques into other systems.
Take pride in learning to write clean, reusable, maintainable and well-tested code.
Demonstrate experience deploying cloud-native applications in AWS or Azure (or a similar cloud platform) – particularly those involving ML models.
Are familiar with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn, PyTorch, Huggingface, …
Have a desire to learn and embrace new and emerging technology.
Are familiar with probabilistic models and understand the mathematical concepts underlying machine learning methods.
For this role, we also strongly value if you:
Have hands on experience in AWS / other cloud environments
Had previous exposure to Natural Language Processing (NLP) problems and have familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, etc.
Can understand and translate between language and methodologies used both in research and engineering fields.
[ Article by: team tosscall ]