Manager, Data Science at Workato
Singapore, , Singapore -
Full Time


Start Date

Immediate

Expiry Date

19 Nov, 25

Salary

0.0

Posted On

20 Aug, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Computer Science, Infrastructure, Python, Leadership Skills, Stream Processing, Statistics, Machine Learning, Communication Skills, Apache Spark, Ml

Industry

Information Technology/IT

Description

ABOUT WORKATO

Workato transforms technology complexity into business opportunity. As the leader in enterprise orchestration, Workato helps businesses globally streamline operations by connecting data, processes, applications, and experiences. Its AI-powered platform enables teams to navigate complex workflows in real-time, driving efficiency and agility.
Trusted by a community of 400,000 global customers, Workato empowers organizations of every size to unlock new value and lead in today’s fast-changing world. Learn how Workato helps businesses of all sizes achieve more at workato.com.

WHY JOIN US?

Ultimately, Workato believes in fostering a flexible, trust-oriented culture that empowers everyone to take full ownership of their roles. We are driven by innovation and looking for team players who want to actively build our company.
But, we also believe in balancing productivity with self-care. That’s why we offer all of our employees a vibrant and dynamic work environment along with a multitude of benefits they can enjoy inside and outside of their work lives.
If this sounds right up your alley, please submit an application. We look forward to getting to know you!

Also, feel free to check out why:

  • Business Insider named us an “enterprise startup to bet your career on”
  • Forbes’ Cloud 100 recognized us as one of the top 100 private cloud companies in the world
  • Deloitte Tech Fast 500 ranked us as the 17th fastest growing tech company in the Bay Area, and 96th in North America
  • Quartz ranked us the #1 best company for remote workers

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

LEADERSHIP 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
  • Ability to balance technical excellence with business pragmatism

SOFT SKILLS / PERSONAL CHARACTERISTICS

  • Experience with AIBrix, vllm or similar ML platform solutions
  • Experience with AI code generation and anonymisation pipelines
  • Knowledge of advanced prompting techniques and prompt engineering
  • Experience building RAG (Retrieval Augmented Generation) systems
  • Background in building ML platforms or infrastructure
  • Familiarity with vector databases (Pinecone, Weaviate, Qdrant)
  • Experience with model security and responsible AI practices
  • Contributions to open-source ML projects
Responsibilities

We are seeking an experienced Data Science / Machine Learning Engineering Lead to join our team and drive the development of advanced ML/AI capabilities. You will lead a team of Data Scientists / ML Engineers, focusing on building and deploying cutting-edge machine learning solutions using our modern ML infrastructure including Anthropic, OpenAI, and self-hosted LLMs.

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