Senior Research Engineer

Key Skills

AWS, Azure, Dask - Python library, Data science techniques, Effective communication skills, Java Programming, JavaScript, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Natural Language Toolkit - NLTK, NumPy, Pandas, Python Programming, Scikit-learn, SciPy, spaCy, TypeScript

Job Description

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.   

About You   

Essential skills & experience  

• Have a Bachelor of Science degree, computer science or related field 

• At least 5 years software engineering experience, ideally in the context of machine learning and natural language processing

• Fluent English

• 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

 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.) 

What's in it For You?

You will join our inclusive culture of world-class talent, where we are committed to your personal and professional growth through:

Hybrid Work Model: We've adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected

Wellbeing: Comprehensive benefit plans; flexible and supportive benefits for work-life balance: flexible vacation, two company-wide Mental Health Days Off; work from another location for up to a total of 8 weeks in a year, 4 of those weeks can be out of the country and the remaining in the country, Headspace app subscription; retirement, savings, tuition reimbursement, and employee incentive programs; resources for mental, physical, and financial wellbeing.

Culture: Globally recognized and award-winning reputation for equality, diversity and inclusion, flexibility, work-life balance, and more.

Learning & Development: LinkedIn Learning access; internal Talent Marketplace with opportunities to work on projects cross-company; Ten Thousand Coffees Thomson Reuters café networking.

Social Impact: Ten employee-driven Business Resource Groups; two paid volunteer days annually; Environmental, Social and Governance (ESG) initiatives for local and global impact.

Purpose Driven Work: We have a superpower that we’ve never talked about with as much pride as we should – we are one of the only companies on the planet that helps its customers pursue justice, truth and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.

Optional - compensation. Compensation may only be relevant for certain positions and is recommended for use primarily by Sales:

Compensation Base salary and a variable compensation that is directly related to your success.

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