Senior Data Scientist (Advanced AI Track)

SINGAPORE AIRLINES LIMITED; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading airline company in Singapore is looking for a generative AI/deep learning expert. This role involves developing advanced machine learning algorithms, mentoring a talented team of data scientists, and collaborating with business units to create impactful AI products. Candidates must have a PhD in a relevant field and substantial work experience in machine learning, as well as excellent programming skills in Python and familiarity with big data processing frameworks. Competitive compensation and opportunities for professional development are offered.

Qualifications

• PhD or exceptional candidates without advanced degrees.
• 3+ years of industry experience in machine learning.
• Strong technical skills in programming and software development.

Responsibilities

• Develop advanced machine learning algorithms.
• Provide technical direction to a skilled data science team.
• Collaborate with business stakeholders on AI products.

Skills

Problem-solving

Programming in Python

Algorithm design/analysis

Big data processing

Mentoring

Education

PhD in computer science, machine learning or related field

Tools

PyTorch

TensorFlow

Spark

Kafka

AWS

Azure

GCP

Job description

Job Description

SIA has multiple positions for generative AI/deep learning experts to drive our AI and data science initiatives.

Key Responsibilities include:

• Member of the in-house AI Center-of-Excellence team that works on challenging problems in advanced AI (including areas on generative multimodal AI, autonomous agent, NLP, computer vision, recommender system), mathematical optimization, game theory, and experimental design.
• Research and develop advanced machine learning algorithms to meet complex product requirements. The scope includes defining hypotheses, executing necessary tests and experiments; evaluating, tuning and optimizing algorithms and methods; and having an eye towards cloud implementation ease, scalability, and robustness in a live customer facing production environment.
• Provide technical direction and guidance to a small and highly skilled team of junior and senior data scientists embedded in Kanban data squads. These squads deliver products/services in generative AI, data science and data analytics to stakeholders in a large number of business units. Serve as a go-to technical expert in your area of AI expertise.
• Work closely with business stakeholders to create impactful and intelligent features/products. Collaborate with other team members including data scientists, data engineers and data strategists. Strategic ownership of all critical end-to-end AI processes.
• Administer/maintain performant cloud and on-premises GPU compute resources that train large ML models and provide inference API microservices in production.

Requirements

• PhD degree related to computer science, machine learning or other AI disciplines is required (consideration will be given to exceptional candidates without advanced degrees).
• Demonstrated intellectual firepower as a rapid problem-solver and tech lead.
• Advanced programming skills in Python. Strong technical skills in algorithm design/analysis, data structure and SQL. At least intermediate-level mastery of functional/object-oriented software development using modern programming languages such as Scala, TypeScript/JavaScript, Java or C# is a must.
• Hands-on proficiency in the use of workflow/map-reduce and stream processing systems such as Spark and Kafka for big-data processing.
• 3 or more years of relevant industry experience as a hands-on technical expert in shallow and deep machine learning, with additional specializations in most of the following areas:

1. Experience in the use of recent proprietary/open-source LLM APIs (such as OpenAI GPT-4, Anthropic Claude 2, Google PaLM 2, or Meta LLaMA 2); software development skills involving multi-agents and prompt engineering using LLM application/data frameworks (such as LlamaIndex and LangChain).
2. Highly conversant with GPU-accelerated deep learning frameworks (such as PyTorch and TensorFlow).
3. Demonstrated ability in rapidly adapting, training and deploying state-of-the-art AI models or services in production based on the latest published research papers and open-source code.
4. Familiarity of Bayesian statistics/inference and Bayesian/causal networks for probabilistic reasoning.

• Significant hands-on experience of AWS, Azure, GCP or other public cloud environment.
• Excellent mentoring, interpersonal and communication skills for working with both technical staff and non-technical business users.
• Experience with Agile/Scrum/Kanban methodologies is a plus.