ML Data Scientist

2 weeks ago

Singapore beBeeDataScience Full time $150,000 - $200,000

Job Overview

We are seeking an experienced Data Science Professional to join our team and take on a challenging role. As a key member of the data science community, you will be responsible for designing and implementing cutting-edge data solutions that drive business growth and innovation.

About the Role

You will own the entire data lifecycle, from data collection and preparation to model development and deployment. Your expertise in machine learning and data analysis will enable you to turn complex data into actionable insights that inform business decisions.

  • Productize Research Prototypes: You will transform research prototypes into high-performance services and APIs that meet business requirements.
  • Evaluation Pipelines: You will design and maintain evaluation pipelines to assess model performance, safety, and fairness.
  • Prompt Optimization Strategies: You will implement strategies to optimize model performance, latency, and cost.
  • Benchmarking Harnesses: You will develop automated benchmarking harnesses to integrate internal and external testing suites.
  • Graduation Criteria: You will define criteria and sign-off checklists to move prototypes to general availability.
  • Monitoring and Alerting: You will build monitoring and alerting systems to track model performance and drive remediation playbooks.
  • Reusable Components: You will contribute reusable internal and open-source evaluation and guardrail components.
  • CI/CD Support: You will support continuous integration and delivery with golden sets, seeded adversarial test packs, and safety regression gates.

Qualifications and Skills

We are looking for a highly skilled data science professional with:

  • 3+ years of experience delivering end-to-end ML/data science solutions.
  • Strong Python skills with knowledge of modern packaging and async patterns.
  • Hands-on experience with LLM integration patterns, PyTorch/TensorFlow, or equivalent.
  • Applied understanding of Responsible AI concepts, including safety, robustness, fairness, and privacy.
  • Cloud and container experience with AWS/GCP/Azure and Docker.
  • Familiarity with vector stores, embedding generation, and prompt/output tracing or observability frameworks.
  • Solid experimental design skills, including statistical validity, variance reduction, and confidence thresholds.
  • Ability to write production-quality code and participate in effective code reviews.
  • Clear communication of technical risk and metric trade-offs to stakeholders.

Preferred Qualifications

We also welcome applicants with experience in:

  • Guardrail or policy frameworks.
  • Adversarial/red-teaming datasets, jailbreak detection, or toxicity/mitigation.
  • Model compression (quantisation, distillation) and GPU/accelerator optimisation.
  • RLHF/DPO/preference optimization or synthetic data generation pipelines.

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