Machine Learning Engineer

Elgada BPO Solutions Inc. is a growing business solution provider based in the heart of Makati, Philippines. We support the ever-growing demands of our offshore client through software development.

Using our tech expertise and cross-industry experience, we evolve digital transformation into digital acceleration. We deliver full-cycle software development services that adapt seamlessly to project requirements and business needs.

Job Summary:

You will work closely with data scientists, software engineers, and product teams to drive AI initiatives across the organization.

Key Responsibilities:

• Design, develop, and deploy machine learning models for classification, regression, NLP, and other applications.
• Fine-tune and customize large language models (LLMs) for specific business needs using domain-specific data.
• Train models using supervised, unsupervised, and reinforcement learning techniques.
• Preprocess and analyze large datasets, ensuring data quality and integrity.
• Implement and monitor ML pipelines, model lifecycle management, and version control.
• Collaborate with engineering teams to integrate ML solutions into scalable production systems.
• Conduct model evaluation, performance tuning, and A/B testing.
• Stay up to date with the latest research and advancements in ML and LLM technologies.

Qualifications:

• Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related field.
• 3+ years of experience in building and deploying machine learning models.
• Solid experience with LLMs (e.g., OpenAI GPT, Google Gemini, LLaMA, Claude, etc.).
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, Transformers (Hugging Face).
• Strong foundation in mathematics, statistics, and algorithm development.
• Experience with data processing frameworks (Pandas, NumPy) and ML Ops tools (e.g., MLflow, Weights & Biases).
• Familiarity with vector databases (e.g., Pinecone, FAISS) and retrieval-augmented generation (RAG) workflows.

Preferred Skills:

• Hands-on experience with prompt engineering and LLM configuration for specific use cases.
• Knowledge of deep learning, computer vision, or time-series analysis.
• Experience with cloud-based ML infrastructure (AWS SageMaker, GCP Vertex AI, Azure ML).
• Familiarity with containerization (Docker, Kubernetes) for model deployment.
• Experience contributing to research or publishing ML papers is a plus.

Additional Benefits:

• HMO on day 1
• Government-mandated benefits
• 13 month pay
• Employee Engagement Events (company outings, fun activities)
• Have the opportunity to work with a team of IT professionals and work directly with the client (US Based - SaaS Company).