AI/ML R&D Engineer

Welocalize

AI/ML Engineer responsible for designing, developing, and implementing machine learning solutions for business processes. Collaborating with teams to ensure project success and ethical AI development.

Posted 6/19/2026full-timeCluj • 🇬🇷 GreeceMid-LevelSeniorWebsite

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

machine learningmachine translationLLM finetuningstatistical analysisPythonTensorFlowPyTorchScikit-learnnatural language processingdeep learning

Soft Skills

project ownershipcommunicationmentoringproblem-solvingteam collaboration

Tools & Technologies

DockerAWSSagemakerEC2S3cloud infrastructureML management technologies

Certifications & Qualifications

BSc in Computer ScienceBSc in MathematicsMaster’s degree

Industry Keywords

supervised learningunsupervised learningreinforcement learningproduction-grade codedeployment strategies

Tech Stack

Tools & technologies

AWSCloudDockerEC2PythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

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
Document diligently and communicate thoughtfully about ML experimentation, design, and deployment

Requirements

What you’ll need

BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus
Minimum 3+ years experience as a Machine Learning Engineer or similar role
Ability to write robust, production-grade code in Python
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
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 ML management technologies and deployment techniques, such as AWS ML offerings, Docker, GPU deployments, etc

Benefits

Comp & perks

Professional development opportunities
Flexible work arrangements