AI Machine Learning Engineer
1 hour ago
About the Role
We are looking for a hands-on AI/ML Engineer who can take an idea from concept to deployment. You will be responsible for designing, developing, training, testing, and integrating machine learning models into core systems.
This role requires a versatile professional skilled in data science, software engineering, and MLOps to deliver end-to-end AI solutions that support business objectives.
What We Offer
- Opportunity to develop and deploy AI solutions end-to-end.
- Autonomy in technical design and implementation.
- Direct impact on key business initiatives.
- Collaborative environment with continuous learning opportunities.
Qualifications
- Bachelor's or master's degree in computer science, Data Science, AI/ML, or a related field.
- 3+ years of experience in applied machine learning or AI engineering.
- Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Experience building and deploying APIs (e.g., FastAPI, Flask, Node).
- Familiarity with cloud services (AWS, GCP, Azure) or containerization (Docker, Kubernetes).
- Practical knowledge of data pipelines (ETL, data versioning, labeling tools).
- Strong understanding of model evaluation and performance tuning
Bonus Skills
- Experience with LLMs, prompt engineering, or LangChain.
- Familiarity with vector databases (Pinecone, FAISS, Milvus).
- Exposure to frontend frameworks (React, Vue) for prototyping.
- Understanding of data security and compliance in regulated domains (e.g., fintech, healthcare).
Key Responsibilities
Data & Model Development
- Collect, clean, and preprocess data for training and testing.
- Design and develop machine learning models (classical ML or deep learning).
- Train, tune, and validate models using real-world datasets.
- Conduct performance testing and error analysis.
System Integration
- Develop APIs or services to integrate the model into the main product or platform.
- Collaborate with backend and frontend developers to embed AI functionality.
- Ensure efficient inference and scalability in production environments.
MLOps & Deployment
- Package and deploy models (e.g., via Docker, FastAPI, or cloud ML services).
- Set up monitoring for model accuracy, drift, and system performance.
- Maintain version control for models and data pipelines.
Collaboration & Documentation
- Work closely with the Product Manager to translate business goals into technical solutions.
- Document models, datasets, and architecture decisions.
- Communicate findings and results clearly to non-technical stakeholders.
Job Type: Full-time
Pay: Php80, Php120,000.00 per month
Benefits:
- Work from home
Work Location: In person
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