AI Engineer

3 hours ago

Taguig, National Capital Region, Philippines Yondu, Inc. Full time $80,000 - $120,000 per year

Company Description

Yondu, a leading IT solutions provider in the Philippines and a subsidiary of Globe Telecom, empowers businesses across various industries with cutting-edge technology solutions to help them thrive in the digital age. With a focus on innovation and growth, Yondu fosters a dynamic and diverse culture that encourages collaboration and professional development. Established in 2001, the company has significantly expanded and supports its employees through upskilling initiatives, certification programs, and flexible work-from-anywhere arrangements. Joining Yondu offers the opportunity to work with knowledgeable professionals to create impactful business solutions while enjoying a rewarding work environment.

KEY RESPONSIBILITIES:

a) Build OpenAI LLM module for RCA, Incident Summary, Correlations and Remediation engine using SOPs, ELK logs and ServiceNow tickets.

b) Build ML Model to detect anomalies in the logs

QUALIFICATIONS:

LLM Model build (primary skill):

a) experience in designing transformer architecture and dynamic prompts using system/user context, templating, and multi-turn chatbot conversational two-way (chatbot) design and also workflow based orchestration.

b) experience in building tokenization, embeddings, prompt engineering, and fine-tuning using Hugging Face Transformers, OpenAI API, LangChain docs.

c) experience in deploying and configuring vector DBs for scalable similarity search, HNSW indexing, sharding, and metadata filtering such as Milvus or Azure AI Search

d) experience in Implementing RAG text chunking strategies (semantic chunking, sliding window, hierarchical chunking) to balance retrieval accuracy and context fit using tolls such as LangChain TextSplitter or LlamaIndex.

Machine Learning Modelling (secondary skill if available) :

a) Feature engineering using Pandas, NumPy, Scikit-learn, Featuretools, PyCare or equavalent

b) Model selection an training for Time-series models (ARIMA, LSTM, Prophet, VAE, etc) and Supervised models (IsolationForest,XGBoost, LightGBM, RandomForest, etc)

c) experience in model ops /deployment using Docker, Kubernetes, MLflow, Airflow, Kubeflow, Azure ML, SageMaker, GitHub Actions or etc.

  • d) Monitoring an ddrift detection using EvidentlyAI, WhyLabs, Prometheus, Grafana, ELK Stack, LangSmith (for GenAI), Weights & Biases or etc

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