Here is an analysis of a research engineer position:
- Do you love creating innovative solutions for customers?
- We are seeking a passionate Sr Research Engineer who will bring expertise in AI and ML and is interested in building data-driven capabilities that drive transformation.
- As a member of Thomson Reuters Labs you will have a direct impact on our company by helping to create new and innovative capabilities that will delight our customers.
- What does Thomson Reuters Labs do?
- We experiment, we build, we deliver. We support the organization and our customers through applied research and the development of new products and technologies. TR Labs innovates collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News.
- As a Senior Research Engineer at Thomson Reuters Labs, you will be part of a global interdisciplinary team of experts. We hire engineers and specialists across a variety of AI research areas to drive the company’s digital transformation. The science and engineering of AI are rapidly evolving. We are looking for an adaptable learner who can think in code and likes to learn and develop new skills as they are needed; someone comfortable with jumping into new problem spaces; who enjoys directing and supporting the efforts of others.
- Is this you? Come join us!
That is perfect. What else?
In this opportunity as a Senior Research Engineer, you will:
- Develop and Deliver: Applying modern software development practices, you will be involved in the entire software development lifecycle, building, testing and delivering high-quality solutions.
- Build Scalable ML Solutions: 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 collaborative team-oriented environment, you will share information, value diverse ideas, partner with cross-functional and remote teams.
- Be an Agile Person: With a strong sense of urgency and a desire to work in a fast-paced, dynamic environment, you will deliver timely solutions.
- 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 dynamic engagement and communication with cross-functional partners and team members, you will effectively articulate ideas and collaborate on technical developments.
Great, what else?
You are a fit for the Senior Research Engineer if your background includes:
- Essential skills & experience:
- A Bachelors Degree in Computer Science or Related Field
- At least 5 years software engineering experience, ideally in the context of machine learning and natural language processing
- Are skilled and have a deep understanding of Python software development stacks and ecosystems, experience with other programming languages and ecosystems is ideal.
- Can understand, apply, integrate and deploy Machine Learning capabilities and techniques into other systems.
- Are familiar with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn
- Take pride in writing clean, reusable, maintainable and well-tested code
- Have a desire to learn and embrace new and emerging technology
- Are familiar with probabilistic models and have an understanding of the mathematical concepts underlying machine learning methods
- Have familiarity with Agile Methodologies.
I check — or have checked — all the boxes. I need to refresh these skills and make public projects since my previous works cannot be disclosed ; or only irrelevant parts.
Preferred skills & experience:
- Experience integrating Machine Learning solutions into production-grade software and have an understanding of ModelOps and MLOps principles
- Demonstrate proficiency in automation, system monitoring, and cloud-native applications, with familiarity in AWS or Azure (or a related cloud platform)
- 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
- Have been successfully taking and integrating Machine Learning solutions to production-grade software
- Hands-on experience in other programming and scripting languages (Java, TypeScript, JavaScript, etc.)
- Have exposure to cloud computing development (AWS/Azure).
- Have familiarity with Agile Methodologies.
Idem.
The objective is to list resources — e.g. projects and certifications — that increases chances of getting a research engineer position in the NLP domain.
The list of resources is:
- This list has been built using our network and the requirements of various job offers in the field.
- The idea is that a threshold will be crossed after which an appropriate job offer will be found.
- The projects are listed in order: each project adds to the previous one — i.e. complexity increases.
- Each project illustrates a maximum of skills.
- Each project is end to end: from development to deployment.
Sources include:
The objective is to list the skills required from job offers similar to a research engineer position.
The skills are:
This list has been compiled from various job offers.
A list of conferences about NLP is:
- ACL
- NAACL (the North American-located chapter of ACL)
- EACL (the European-located chapter of ACL)
- EMNLP
- COLING
- AAAI/ICLR/ICML (these concern AI/ML in general, but some NLP papers are accepted)
The list has been found from various sources, 6.861* Quantitative Methods for NLP in particular.
This profile is an application file tailored specifically for Data Science/NLP positions. It is formed by:
- English CV (PDF)
- French CV (PDF)
- GitHub
- Application file (on demand).
This profile is derived from the current profile. The most important addition are the projects and certifications added to the GitHub profile and application file.