AI Engineer
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Key details
- Salary
- ₱1M/yr
- Location
- Manila, Philippines
- Work style
- Remote
- Level
- Mid level
- Job type
- Full-time
- Experience
- 3–6 yrs
- Function
- Data & ML
- Focus area
- AI / ML
- Posted
- Yesterday
Skills
About the role
Salary : Up to PHP 120,000/month
Working Hours & Conditions: Observing AU working hours
Holidays : Observing AU holidays
A leading technology consulting and digital transformation firm is seeking a skilled AI Engineer to design, build, and deploy production-grade artificial intelligence and machine learning solutions for enterprise clients. In this role, you will bridge the gap between cutting-edge AI innovation and real-world application, translating complex client business challenges into scalable, high-performing intelligent systems. You will work closely with cross-functional consulting and engineering teams to integrate foundation models, build robust data pipelines, and ensure optimal system reliability across diverse client environments.
RESPONSIBILITIES:
- Design & System Architecture: Architect, build, and maintain production-ready AI pipelines, APIs, and microservices for seamless model integration into client platforms and applications.
- Model Implementation & Fine-Tuning: Integrate pre-trained large language models (LLMs), natural language processing (NLP), and advanced machine learning algorithms, optimizing and fine-tuning them for specific client domains.
- Data Pipeline Engineering: Develop and maintain scalable data ingestion, transformation, and vector indexing pipelines (RAG systems) to support real-time enterprise inference and training workflows.
- Performance Optimization: Monitor, evaluate, and benchmark model performance, accuracy, latency, and resource consumption in production enterprise environments.
- Client & Cross-Functional Collaboration: Partner with product managers, backend engineers, consultants, and stakeholders to frame technical problems, define model requirements, and execute deployment strategies.
- Quality & Security Assurance: Implement guardrails, evaluation frameworks, and testing procedures to ensure model safety, reliability, and enterprise data privacy compliance.
Requirements
- Experience: 3+ years of professional software engineering experience with a strong focus on machine learning systems, enterprise software, or AI application development.
- Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field (or equivalent practical experience).
- Core Programming: Advanced proficiency in Python, alongside experience with standard backend languages (e.g., Node.js, Go, or Java).
- AI & Machine Learning Frameworks: Hands-on experience with modern AI frameworks and libraries (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face).
- Database & Vector Search: Proficiency with relational databases (PostgreSQL/MySQL), NoSQL data stores, and vector databases (e.g., Pinecone, Weaviate, Qdrant, or pgvector).
- Deployment & Cloud Infrastructure: Strong experience deploying models to cloud platforms (AWS, GCP, or Azure) using Docker, Kubernetes, and serverless compute.
DESIRED (NOT REQUIRED):
- Experience building retrieval-augmented generation (RAG) architectures and multi-agent AI systems for enterprise clients.
- Familiarity with model optimization techniques (quantization, pruning, continuous batching, vLLM).
- Knowledge of MLOps practices, model monitoring tools (e.g., MLflow, Weights & Biases, LangSmith), and CI/CD pipelines.
- Strong consulting aptitude with exceptional communication skills to explain complex technical tradeoffs to non-technical business stakeholders.
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