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.
Job Reference: #LI-JC1
Job Profile Summary:
The Machine Learning Engineer role is responsible for the development and implementation of reliable AI systems. This includes integrating AI/ML models into real workflows, as well as supporting deployment and maintenance.
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.
in 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.
Job Description:
MAIN TASKS & RESPONSIBILITIES:
The following is a non-exhaustive list of responsibilities and areas of ownership of an AI/ML Engineer
- Build, maintain, and improve Python services and pipelines for AI workloads.
- Follow solid engineering principles. Produce clean, well tested, and production-ready code.
- Own projects from implementation to deployment, ensuring stability and performance.
- Deploy AI models and algorithms using appropriate techniques and technologies, such as containerization using Docker and deployment to cloud infrastructure (AWS).
- Run experiments, evaluate results, and interpret performance metrics.
Success Indicators for a Machine Learning Engineer
- You deliver robust, maintainable Python code.
- AI models run reliably in production with clear performance metrics.
- You collaborate effectively with teammates and communicate issues early.
- You continuously refine workflows, tooling, and code quality.
REQUIREMENTS
Education
BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus
Experience
- Minimum 3+ years experience as a Machine Learning Engineer or similar role
Skills & Knowledge
- Strong Python programming skills (testing, packaging, debugging, performance-aware coding).
- Experience building production systems or pipelines.
- Comfortable with Docker and cloud environments (AWS).
- Ability to take ownership of tasks and manage projects end-to-end.
- Excellent communication and documentation skills.
- Knowledge of AI techniques and algorithms, including embeddings, LLMs as a judge, etc.