Job Description
- Fine-tune and optimize existing open-source LLMs (e.g., Code LLaMA, StarCoder) for code related tasks (completion, explanation, refactoring, bug fixing).
- Process and manage large-scale, multi-language code datasets (cleaning, deduplication, quality filtering) using distributed frameworks.
- Implement Retrieval-Augmented Generation (RAG) pipelines with vector databases for code and technical document retrieval.
- Optimize model inference performance (quantization, distillation, GPU acceleration) for low latency servings.
- Develop APIs/microservices to integrate AI features into IDE extensions (VS Code API, TypeScript).
- Monitor and evaluate model performance using code-specific metrics .
- Collaborate with Data Engineers, Product, and DevOps to ensure high-quality data, scalable deployment, and stable production performance.
- Write clean, maintainable code, manage version control (Git), and document experiments and deployment processes.
Job Requirements
Mandatory
- Bachelor’s degree in Computer Science, AI/ML, Data Engineering, or related field.
- 2–5 years of experience in AI/ML, with at least 1 year working on LLM-driven systems or AI Agents.
- Proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
- Hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel).
- Familiarity with vector databases (Pinecone, Weaviate, FAISS) and RAG architectures.
- Experience with Docker, GitLab CI/CD (or similar), and cloud AI/ML services (AWS, GCP, Azure).
- Understanding of distributed or big data processing tools (Spark, Dask, Ray).
- Good English communication skills and ability to work in cross-functional teams.
Nice to have:
- Experience with multi-agent systems and coordination strategies.
- Familiarity with TypeScript and building APIs/IDE integrations for AI-powered tools.
- Knowledge of advanced embeddings (AST parsing, syntax-aware embeddings, knowledge graphs).
- Experience with MLOps/AgentOps tools (MLflow, W&B, Guardrails, Kubeflow).
- Contributions to open-source projects in AI Agents, LLMOps, or coding assistants.
How To Apply
Step 1: Submit Your CV
Apply directly through the Innotech Vietnam Corporation website by uploading your updated CV to the careers section.
Step 2: Phone Screening
If shortlisted, you will receive a call from the HR team for a brief survey and initial screening.
Step 3: Interview
Qualified candidates will be invited to an interview to further assess suitability for the role.
Step 4: Onboarding
Successful applicants will receive an offer and begin the onboarding process to officially join the team.
