As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Summary:
The Senior Machine Learning Engineer role is responsible for the discovery, 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, MLFlow, and other tools. The role also includes responsibility for establishing best practices with which to optimize and measure the performance of our models and algorithms against business goals.
The Senior Machine Learning Engineer provides guidance and support to all members of the ML team. The Senior Machine Learning Engineer is an educator in, and ambassador for, ML with a sphere of influence extending to senior & executive leadership.
Responsibilities
- Design and develop machine learning models and algorithms for various aspects of the localization and business workflow processes, including machine translation, LLM fine tuning, and quality assurance.
- Take ownership of key projects from conception to deployment, ensuring that they meet business requirements and maintain momentum and direction until delivery.
- Collaborate with developers, data engineers, and business process stakeholders to gather requirements and identify areas for improvement.
- Evaluate and select appropriate machine-learning techniques and algorithms to solve specific problems.
- Deploy machine learning models into a large-scale AWS environment, including architecture design and deep knowledge of AWS best practices.
- Implement and optimize machine learning models and technologies using Python, TensorFlow, Pandas, and similar.
- Perform statistical analysis and fine-tuning using test results.
- Provide guidance and support to members of the team, mentoring in best practices for machine
- learning management.
Requirements and Skills
- 5+ 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, and 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.
- Significant experience with ML management technologies and deployment techniques. Must include enterprise experience with AWS and Docker. Examples of relevant (but not required) AWS services: Amazon Sagemaker, EC2, Lambdas, DynamoDB, RedShift.
Education
- BS in Computer Science, Mathematics, or similar field;
- Master’s degree is a plus.
