AI Machine Learning R&D Engineer, Welocalize
More information about location
Translation & localization for global businesses
Open for applications
Translation & localization for global businesses
1001+ employees
Open for applications
More information about location
1001+ employees
Company mission
To bridge language and AI to power global success in even the most complicated and regulated environments.
Role
Who you are
- Master degree in Computer Science, Data Science, Engineering, Mathematics or similar field; PhD is a plus
- Minimum 3+ years experience as a Machine Learning Engineer or similar role
- Ability to write robust, production-grade code in Python
- Excellent communication and documentation skills
- Strong knowledge of machine learning techniques and algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning
- Hands-on, high proficiency experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn
- Experience with natural language processing (NLP) techniques and tools
- Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders
- Experience taking ownership of projects from conception to deployment, and mentoring more junior team members
- Hands-on experience with AWS technologies including EC2, S3, and other deployment strategies. Experience with SNS, Sagemaker a pls
- Experience with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, GPU deployments, etc
What the job involves
- The AI Machine Learning Research & Development Engineer role is responsible for the design, development and implementation of machine learning solutions to serve our organization
- This includes ownership or oversight of projects from conception to deployment with appropriate AWS services, Docker, ML Flow, and other
- The role also includes responsibility for following best practices with which to optimize and measure the performance of our models and algorithms against business goals
- The following is a non-exhaustive list of responsibilities and areas of ownership of an AI/ML R&D Engineer
- Design and develop machine learning models and algorithms for various aspects of the localization and business workflow processes, including machine translation, LLM finetuning, and quality assurance
- Take ownership of key projects from definition to deployment, ensuring that they meet technical requirements and maintain momentum and direction until delivery
- Evaluate and select appropriate machine-learning techniques and algorithms to solve specific problems
- Implement and optimize machine learning models and technologies using Python, TensorFlow, and other relevant tools and frameworks
- Perform statistical analysis and fine-tuning using test results
- Deploy machine learning models and algorithms using appropriate techniques and technologies, such as containerization using Docker and deployment to cloud infrastructure
- Use AWS technologies (including but not limited to Sagemaker, EC2, S3) to deploy and monitor production environments
- Keep abreast of developments in the field, with a dedication to learning in the role
- Document diligently and communicate thoughtfully about ML experimentation, design, and deployment
- Project scope: Define and design solutions to machine learning problems. Integration with larger systems done with the guidance of more senior engineers
- Success Indicators for a Machine Learning Engineer
- Effective Model Development: Success is evident when the models developed are accurate, efficient, and align with project requirements
- Positive Team Collaboration: Demonstrated ability to collaborate effectively with various teams and stakeholders, contributing positively to project outcomes
- Continuous Learning and Improvement: A commitment to continuous learning and applying new techniques to improve existing models and processes
- Clear Communication: Ability to articulate findings, challenges, and insights to a range of stakeholders, ensuring understanding and appropriate action
- Ethical and Responsible AI Development: Adherence to ethical AI practices, ensuring models are fair, unbiased, and responsible
Our take
According to the CSA, while only 16% of the global population speaks English as their native language, approximately 60% of the top 10M websites are in English. With over 250 language options, Welocalize enables companies to unlock business opportunities at a global scale by transforming and localizing its clients’ online websites and content.
The company has made an impressive number of strategic acquisitions over the years, widening its reach across a range of industries including digital content marketing, litigation support, and healthcare, and is a trusted multilingual solution for 2,000+ global company clients (including Disney, Uber, Dell, TNT, and Blackboard).
Founded in 1997, the company is currently the 4th largest language service provider in North America and the 9th largest provider globally. Welocalize is well-positioned to see continued growth as it furthers its market-leading presence, including by making moves to strengthen its leadership team moving forward.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
28% employee growth in 12 months
Company
Funding (1 round)
Nov 2010
$34m
GROWTH EQUITY VC
Total funding: $34m
Company HQ
Midtown South, New York, NY
Leadership
Paul Carr
(CEO)Prior to joining Welocalize in 2023, Paul was a President at Third Bridge Group for 4 years and a President at Axiom for 10 years. He also spent 4 years at American Express as a VP and Head of Strategy/GM of International Insurance Services.
Chris Grebisz
(CTO)Chris joined Welocalize in 2002, leaving the team in 2008 to work in leadership roles at various Software Development companies. He then returned to Welocalize in 2013 and has since led operations in the Americas and now oversees the companies digital transformation and technology development worldwide.
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