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AI/ML R&D Engineer
WelocalizeAI/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.
Tech Stack
Tools & technologiesAWSCloudDockerEC2PythonPyTorchScikit-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
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningmachine translationLLM finetuningstatistical analysisPythonTensorFlowPyTorchScikit-learnnatural language processingdeep learning
Soft Skills
project ownershipcommunicationmentoringproblem-solvingteam collaboration
Certifications
BSc in Computer ScienceBSc in MathematicsMaster’s degree