Applied Ml Scientist

1 week ago

Bengaluru Karnataka, India Thomson Reuters Full time

Applied Machine Learning Scientist
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 in close collaboration with the Product and Engineering teams. TR Labs innovates collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News. In addition to this co-development and innovation, we also invest in long term research that can shape the future for our products and customers.
As an Applied Machine Learning Scientist in TR Labs, you will be part of a global interdisciplinary team of experts. We hire specialists and generalists across a variety of AI research areas, as well as Engineering and Design, to drive the company’s digital transformation. TR Labs is known for delivering innovative AI products that serve Thomson Reuters customers in new and exciting ways.

About the role
As an Applied Machine Learning Scientist, you will:
Collaborate: Working on a collaborative cross-functional team, you will share information, value diverse ideas, and partner effectively with colleagues across the globe.
Deliver: With a sense of urgency and the desire to work in a fast-paced, dynamic environment, you will connect complex business requirements with development deliverables. Our problems are complex; our solutions are right-sized. You will be accountable for timely, well-managed deliverables.
Innovate: You will be empowered to try new approaches and learn new technologies. You will foster innovative ideas to solve real-world challenges. You will iterate to improvement rapidly with a mindset for failing fast and learning continuously from data.
Inspire: You will be a proactive communicator who is excited to share your work. You will be articulate and compelling in describing ideas to both technical and non-technical audiences.

About you

Basic qualifications
Master’s or Bachelor’s with a comparable level of experience (3+ years for Master’s or 6+ years for Bachelor’s) or PhD in a relevant discipline
Proficiency in Python
Experience with Natural Language Processing, and/or Machine Learning methods including Deep Neural Networks
Software engineering and / or data engineering skills for prototyping
Experience as a technical contributor in aspects of the following:comfort in dealing with uncertainty and ambiguity in problem statements and paths to success
executing the research and development with an iterative mindset and approach
communication of progress and plans with varied stakeholders

Preferred qualifications
5+ years practical experience using AI and ML to solve diverse and/or ambiguous problems in academia or industry
Have familiarity with common NLP use cases such as chatbot development and information retrieval (RAG), language translation, named entity recognition, summarization and topic modeling.
Familiarity with LLM training and efficient finetuning (PEFT)
Experience with NLP/CV libraries such as PyTorch, TensorFlow, Scikit-learn, spaCy, HuggingFace Transformers, OpenAI, LangChain, Semantic Kernel & OpenCV
Experience in using Cloud solutions (AWS,Azure,etc.) for building and deploying data science solutions
Experience in a fast-paced, agile environments managing uncertainty and ambiguity
Outstanding communication and data-driven decision-making collaboration with Product + Business Stakeholders
Diverse experiences across problem spaces, companies and cultures

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:
Technology: Our Scientists and Engineers get to play with big data sets to discover new products, capabilities, and insights for our customers. Thomson Reuters is most well-known for the globally respected Reuters News agency, but our company is also the leading source of information for legal, corporate and tax professionals. We have over 60,000 TBs worth of legal, regulatory, news, and tax data.
Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) 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: global minimum parental leave, 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; enterprise-wide company learning days,

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