This job is closed
We regret to inform you that the job you were interested in has been closed. Although this specific position is no longer available, we encourage you to continue exploring other opportunities on our job board.
About the position
The Senior Research Engineer at Thomson Reuters Labs is responsible for creating innovative AI and ML solutions that enhance customer experiences. This role involves collaborating with a global team to develop scalable machine learning systems and contribute to the company's digital transformation efforts. The engineer will engage in the entire software development lifecycle, from building to delivering high-quality solutions, while fostering a culture of innovation and effective communication within cross-functional teams.
Responsibilities
- Develop and deliver high-quality software solutions throughout the software development lifecycle.
- Build scalable machine learning solutions and large-scale data processing pipelines.
- Collaborate in a team-oriented environment, sharing information and valuing diverse ideas.
- Work in a fast-paced, dynamic environment to deliver timely solutions.
- Contribute innovative ideas and solutions, accountable for end-to-end deliveries.
- Effectively communicate and engage with cross-functional partners and team members.
Requirements
- Bachelor's Degree in Computer Science, Related Field, or Equivalent Experience.
- At least 5 years of software engineering experience.
- At least 2 years working on a Machine Learning related product or solution.
- Deep understanding of Python software development stacks and ecosystems.
- Ability to write clean, reusable, maintainable, and well-tested code.
- Desire to learn and embrace new and emerging technology.
- Ability to collaborate and communicate effectively in a multi-disciplinary team.
- Experience with cloud computing development.
- Experience with Agile Methodologies.
- Experience implementing CI/CD, DevOps, and SDLC concepts.
Nice-to-haves
- Experience integrating Machine Learning solutions into production-grade software.
- Understanding of ModelOps and MLOps principles.
- Exposure to Natural Language Processing (NLP) problems and familiarity with tasks like Named Entity Recognition (NER).
- Hands-on experience in other programming languages or scripting languages (Java, Rust, Scala, Typescript, etc.).
Benefits
- Hybrid Work Model with flexible working environment.
- Comprehensive benefit plans for work-life balance.
- Flexible vacation and two company-wide Mental Health Days Off.
- Work from another location for up to 8 weeks a year.
- Headspace app subscription for mental wellbeing.
- Retirement and savings plans, tuition reimbursement, and employee incentive programs.
- Access to LinkedIn Learning and internal Talent Marketplace for professional development.
- Two paid volunteer days annually and support for ESG initiatives.
