Data Science Innovation Manager

2 weeks ago

Singapore beBeeDataScience Full time $180,000 - $250,000
Lead Data Science Innovation

We are seeking an experienced Data Science/Machine Learning Engineering Lead to join our team and drive the development of advanced ML/AI capabilities.

As a leader in your field, you will be responsible for building and deploying cutting-edge machine learning solutions using our modern ML infrastructure including Anthropic, OpenAI, and self-hosted LLMs.

Team Leadership & Management
Lead, mentor, and develop a team of Data Scientists, Data Engineers, and ML Engineers.
Conduct regular 1:1s, performance reviews, and career development planning.
Foster a collaborative, innovative team culture focused on continuous learning and knowledge sharing.
Coordinate work allocation and ensure timely delivery of projects.
Facilitate knowledge sharing and best practices across the team.Technical Leadership
Design and implement scalable ML model training pipelines using modern tools (e.g., MLflow, Comet, Langfuse, WandB, Trino, dbt, Spark, Flink, etc.).
Lead fine-tuning initiatives for both commercial (Anthropic Claude, OpenAI GPT) and open-source LLMs.
Utilize self-hosted LLM infrastructure using Ray, AIBrix, and vLLM for optimal performance and cost efficiency with Lora/QLora.
Architect and oversee model continuous validation frameworks within our ecosystem.
Develop real-time anomaly detection systems leveraging streaming data processing.
Build predictive models for system performance, usage patterns, and automation workflow optimization.Strategic Initiatives
Optimize the balance between commercial APIs (Anthropic, OpenAI) and self-hosted models for different use cases.
Partner with product and engineering teams to identify high-impact ML opportunities.
Define the team's technical roadmap aligned with company objectives.
Drive adoption of state-of-the-art ML techniques and tools.
Contribute to infrastructure decisions for scaling our ML platform.Operational Excellence
Implement robust CI/CD pipelines for ML models in Kubernetes environments.
Monitor model performance using MLflow tracking and implement drift detection.
Manage Flink jobs for real-time feature engineering and anomaly detection.
Document processes, architectures, and decision rationale.RequirementsQualifications / Experience / Technical Skills
Education & Experience
Master's or PhD in Computer Science, Machine Learning, Statistics, or related field.
10+ years of hands-on experience in data science/machine learning.
5+ years of experience leading technical teams.
Proven track record of deploying ML & LLM models to production at scale.Technical Skills
Deep expertise in Python and ML frameworks (PyTorch, TensorFlow).
Extensive experience with commercial LLM APIs (Anthropic Claude, OpenAI GPT-4).
Strong proficiency with MLflow for experiment tracking and model management.
Experience with distributed computing using Apache Spark.
Proficiency with Apache Flink for stream processing and real-time ML.Knowledge of LLM fine-tuning techniques (LoRA, QLoRA, full fine-tuning).
Expertise in anomaly detection algorithms and time series analysis.Leading Skills
Demonstrated ability to lead and inspire technical teams.
Strong communication skills to translate complex technical concepts to stakeholders.
Experience with agile development methodologies.
Track record of successful cross-functional collaboration.Benefits
A vibrant and dynamic work environment along with a multitude of benefits employees can enjoy inside and outside of their work lives.
A flexible, trust-oriented culture that empowers everyone to take full ownership of their roles.
Opportunities for professional growth and development.
Collaborative team environment.Interview ProcessIf this opportunity sounds right up your alley, please submit an application.

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