Lead Machine Learning Engineer

hace 2 meses

Ciudad de México, Ciudad de México Thomson Reuters A tiempo completo

Position Overview

As a Senior Applied AI professional at Thomson Reuters, you will:

  • Design and Implement: Engage in the complete software development lifecycle, utilizing contemporary software engineering methodologies to construct, evaluate, and deploy superior solutions.
  • Create Robust ML Frameworks: Develop extensive data processing architectures that empower researchers to innovate and refine advanced machine learning models. Your focus will be on crafting high-efficiency systems suitable for expansive online environments.
  • Collaborate Effectively: Thrive in a cooperative, team-centric atmosphere where you will exchange insights, appreciate diverse perspectives, and collaborate with cross-functional and remote teams.
  • Embrace Agility: With a proactive mindset and a commitment to working in a fast-paced, dynamic setting, you will ensure timely delivery of solutions.
  • Foster Innovation: You will be encouraged to explore new methodologies and technologies, contributing creative solutions and taking ownership of comprehensive project deliveries.
  • Communicate Effectively: Engage dynamically with cross-functional partners and team members, articulating concepts clearly and collaborating on technical advancements.

Candidate Profile

  • Possess a Bachelor’s degree in Computer Science or a related discipline.
  • Bring a minimum of 5 years of software engineering experience, preferably within machine learning and natural language processing domains.
  • Demonstrate expertise in Python development environments, with familiarity in additional programming languages being advantageous.
  • Have the capability to comprehend, apply, and integrate machine learning techniques into various systems.
  • Be well-versed in the Python data science ecosystem, including libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, and scikit-learn.
  • Take pride in producing clean, reusable, maintainable, and thoroughly tested code.
  • Exhibit a strong desire to learn and adapt to emerging technologies.
  • Understand probabilistic models and the mathematical principles underpinning machine learning methodologies.
  • Have experience in deploying machine learning solutions in production environments, with knowledge of ModelOps and MLOps practices.
  • Show proficiency in automation, system monitoring, and cloud-native applications, with experience in AWS or Azure.
  • Possess prior exposure to Natural Language Processing challenges, with familiarity in tasks such as Named Entity Recognition (NER), Information Extraction, and Information Retrieval.
  • Be capable of translating between research and engineering terminologies and methodologies.
  • Have successfully integrated machine learning solutions into production-grade software.
  • Possess hands-on experience with other programming and scripting languages (Java, TypeScript, JavaScript, etc.).

Benefits

At Thomson Reuters, we recognize that our employees are our most valuable asset. We offer a range of benefits to support your personal and professional development:

  • A casual and inclusive office culture with colleagues from over 30 countries.
  • Competitive compensation package.
  • Flexible hybrid work arrangements.
  • Additional time off for volunteer activities.
  • Comprehensive wellbeing program, including private healthcare, pension plans, and more.
  • Commitment to high ethical standards in the workplace.
  • Opportunities for learning and development through company-sponsored programs.
  • A unique perspective on Thomson Reuters: Thomson Reuters Labs serves as a microcosm of the entire organization, providing:
  • Accelerated growth in cross-business insights.
  • A rich internal network, including access to senior leadership across various customer segments and functions.

Accessibility

As a global organization, we depend on a diverse range of cultures and ideas to achieve our objectives. We are committed to attracting talented individuals from all backgrounds, ensuring equal opportunity in our hiring practices.

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