Advanced AI Solutions Developer

7 days ago

Singapore beBeeArtificial Full time $90,000 - $120,000
AI Solutions Engineer

Our ideal candidate will be responsible for designing and developing advanced AI solutions to drive business growth and enhance customer experiences. Proactive identification and engagement with high-value opportunities are essential skills for this role.

Key Responsibilities:
  • Developing end-to-end AI solutions that meet client needs and strategic goals
  • Conducting in-depth assessments of client data infrastructure and providing actionable recommendations for improvement
  • Rapidly developing functional AI prototypes and proof-of-concepts that adhere to best practices for maintainability and production readiness
  • Collaborating effectively with the internal AI Production team to ensure seamless integration into the full development lifecycle
Required Skills and Qualifications:

Minimum Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field. Master's or Ph.D. preferred.

3+ years of progressive experience in AI/ML solution design, data science, or AI engineering, with a significant portion in a client-facing or consulting capacity.

Expert proficiency in Python and extensive experience with core AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). Strong practical experience with Google Cloud Platform (GCP) services relevant to AI/ML (e.g., Vertex AI, BigQuery, Cloud Storage, Dataflow, Cloud Functions).

Proficiency with Docker for containerization and a foundational understanding of container orchestration (e.g., Kubernetes concepts for GKE). Solid understanding of MLOps principles for reproducibility, experiment tracking (e.g., MLflow, Vertex AI ML Metadata/Model Registry), and model versioning.

High-level expertise in data governance frameworks, data quality assessment (including tools/libraries like Great Expectations), metadata management (e.g., Google Cloud Data Catalog), and data architecture principles.

Strong expertise in distributed computing and parallel processing techniques is vital for handling large-scale AI workloads.

Excellent presentation, documentation, and stakeholder management skills.

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