AI Engineer (Full-Stack)

TOTAL EBIZ SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

A technology solutions firm based in Singapore is seeking a Machine Learning Engineer to optimize AI solutions. Candidates should have a Bachelor's Degree in Computer Science or Data Science, with at least 2 years in data-heavy roles focusing on machine learning. Proficiency in Python and familiarity with tools like TensorFlow and AWS are crucial. The ideal candidate will work collaboratively within a team and have a strong analytical mindset, ensuring effective solution delivery.

Qualifications

• Bachelor's Degree or higher in Computer Science, Data Science, or related disciplines.
• At least 2 years of relevant experience in machine learning engineering, data science, or data engineering.
• Proficiency in common machine learning algorithms and key parameters.
• Developing and optimising machine learning models using Python packages like scikit-learn, TensorFlow, or PyTorch.
• Experience with SQL and vector databases for similarity search.
• Working with cloud infrastructure like MS Azure or AWS.
• Understanding of containerization technologies such as Docker and orchestration platforms like Kubernetes.
• Capable of architecting secure and scalable machine learning solutions.
• Capable of ensuring high data quality standards in collected data.

Responsibilities

• Work well in cross-functional teams with engineers and data scientists.
• Strong analytical thinking and eagerness to learn new technologies.
• Strong communication skills and collaborative work.

Job description

Requirements

• Bachelor's Degree or higher in Computer Science, Data Science, or related disciplines. We will also factor in relevant certifications (e.g., Coursera).
• At least 2 years of relevant experience, in machine learning engineering, data science, data engineering, or other data-heavy roles, and proficiency in the following:
• Common machine learning algorithms and key parameters, Natural Language Processing, Knowledge-based Systems (KBS) and Generative AI projects.
• Developing and optimising machine learning or AI models using common Python packages such as scikit-learn, TensorFlow, or PyTorch.
• SQL and/or experience working with vector databases (such as Pinecone,Weaviate, Chroma, or similar) for similarity search, embeddings storage, andretrieval-augmented generation (RAG) applications.
• Working with cloud infrastructure and services to deploy machine learningmodels, pipelines, or solutions (e.g. MS Azure/AWS)
• Containerization technologies such as Docker and orchestration platforms like Kubernetes, with a strong understanding of deploying and managing machine learning models in containerized environments.
• Capable of architecting machine learning or AI solutions that meet the users’needs while being effective, reliable, secure, scalable, and cost-efficient.
• Capable of cleaning, imputing, and correcting anomalies in the collectedstructured or unstructured data to ensure high data quality standards.

• Ability to work well in cross-functional and interdisciplinary teams, e.g with engineers and data scientists in development and training of ML models.
• Strong analytical thinking and eagerness to learn and share new technologies with team members
• Strong communication skills and ability to work collaboratively

Preferences

• Understanding or experience in machine learning or AI governance, especially in explainability and fairness.
• Experience in delivery of machine learning or AI solutions for internal teams or external clients.