FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Machine Learning Engineer – AI Pretraining Fundamentals
qode.world. Design, develop, and deploy agentic AI systems leveraging LLMs for complex, multi-step reasoning tasks .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying agentic AI systems using LLMs, with a strong focus on optimizing models through Supervised Fine-Tuning and LoRA techniques. Proficient in AWS AI/ML services and capable of integrating deep learning models into product ecosystems while effectively communicating with diverse stakeholders.
Highest-signal resume keywords
Machine LearningDeep LearningLLM ExpertiseAWS AI/ML ServicesPyTorch or TensorFlow
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Supervised Fine-TuningLoRA TechniquesModel OptimizationError AnalysisIterative Improvements
Soft Skills
Excellent Communication SkillsCollaborationIndependent Work
Tools & Technologies
AWS SageMakerAWS BedrockAWS LambdaAWS EC2
Industry Keywords
Agentic AI SystemsDeep Learning ModelsAgile EnvironmentCross-Functional Collaboration
Tech Stack
Tools & technologiesAWSEC2PyTorchTensorflow
About the role
Key responsibilities & impact- Design, develop, and deploy agentic AI systems leveraging LLMs for complex, multi-step reasoning tasks
- Execute Supervised Fine-Tuning (SFT) and implement LoRA techniques to optimize models for domain-specific applications
- Architect and maintain scalable machine learning pipelines on AWS
- Ensure high availability and performance of Generative AI services
- Collaborate with cross-functional teams to integrate deep learning models into existing product ecosystems
- Monitor model performance and conduct error analysis
- Implement iterative improvements to enhance accuracy and reliability
- Communicate technical concepts and project progress to technical and non-technical stakeholders in English and Vietnamese
Requirements
What you’ll need- 4-5+ years of professional experience in Machine Learning, Deep Learning, and AI development
- Knowledge of pretraining fundamentals
- Proven expertise working with LLMs, including SFT and LoRA fine-tuning methodologies
- Strong proficiency in AWS AI/ML services, including SageMaker, Bedrock, Lambda, and EC2
- Deep understanding of PyTorch or TensorFlow
- Experience building agentic workflows and integrating external tools/APIs with LLMs
- Excellent verbal and written communication skills in both English and Vietnamese
- Ability to work independently and collaboratively in an agile environment with a focus on rapid delivery
- Ability to join the team within 1-2 weeks
Benefits
Comp & perks- Competitive compensation package
- Opportunities for professional growth
- Chance to work on state-of-the-art Generative AI projects