Total 7 Information Technology job vacancies

Summary

The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing. The features we create are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. We also develop innovative generative AI technologies based on Large Language Model to power innovative features in both Apple’s devices and services on the cloud.

As part of this group, you will be doing large scale machine learning and deep learning to improve Query Understanding and Ranking of search and developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning models, using word embeddings and deep learning to understand the quality of matches, online learning to react quickly to change, natural language processing to understand queries, taking advantage of petabytes of data and signals from millions of users and combining information from different sources to provide the user with results that best satisfies their intent and information seeking needs.

You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple’s AI powered products, also conduct applied research to transfer the groundbreaking research in generative AI to production ready technologies.

Description

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for people with excellent applied machine learning, NLP experience and solid engineering skills in creating outstanding search and NLP services. This role will have the following responsibilities:

• Analyzing search ranking and relevance requirements, issues and opportunities
• Developing, fine-tuning, and evaluating domain specific Large Language Models for various tasks and applications in Apple’s AI powered products
• Conducting applied research to transfer the pioneering research in generative AI to production ready technologies
• Understanding product requirements, translate them into modeling tasks and engineering tasks
• Building machine learned models for search relevance, ranking and query understanding problems
• Integrating search functions into Apple products, such as Siri, Spotlight, Safari, Messages, Lookup, etc.
• Building end-to-end production system including query understanding and ranking to power search
• Applying Spark, Hadoop MapReduce, Hive, Impala to perform distributed data processing

Minimum Qualifications

• PhD, MS or equivalent experience
• Experience in machine learning, deep learning, information retrieval, natural language processing or data mining
• Experience of prompt engineering, fine-tuning, evaluating, and developing data collection/annotation/management tooling for LLMs.
• Proficiency in one of following languages: Python, Go, Java, C++

Preferred Qualifications

• Excellent data analytical skills
• Good interpersonal skills and team player
• PhD preferred

Apple is an equal opportunity employer that is committed to inclusion and diversity, and thus we treat all applicants fairly and equally. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.

Summary

The AIML Information Intelligence team is creating groundbreaking technology for artificial intelligence, machine learning and natural language processing. The features we create are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. We also develop innovative generative AI technologies based on Large Language Model to power innovative features in both Apple’s devices and services on the cloud.

As part of this group, you will be doing large scale machine learning and deep learning to improve Query Understanding and Ranking of search and developing fundamental building blocks needed for Artificial Intelligence. This involves developing sophisticated machine learning models, using word embeddings and deep learning to understand the quality of matches, online learning to react quickly to change, natural language processing to understand queries, taking advantage of petabytes of data and signals from millions of users and combining information from different sources to provide the user with results that best satisfies their intent and information seeking needs.

You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain specific Large Language Models for various tasks and applications in Apple’s AI powered products, also conduct applied research to transfer the groundbreaking research in generative AI to production ready technologies.

Description

As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for people with excellent applied machine learning, NLP experience and solid engineering skills in creating outstanding search and NLP services. This role will have the following responsibilities:

• Analyzing search ranking and relevance requirements, issues and opportunities
• Developing, fine-tuning, and evaluating domain specific Large Language Models for various tasks and applications in Apple’s AI powered products
• Conducting applied research to transfer the pioneering research in generative AI to production ready technologies
• Understanding product requirements, translate them into modeling tasks and engineering tasks
• Building machine learned models for search relevance, ranking and query understanding problems
• Integrating search functions into Apple products, such as Siri, Spotlight, Safari, Messages, Lookup, etc.
• Building end-to-end production system including query understanding and ranking to power search
• Applying Spark, Hadoop MapReduce, Hive, Impala to perform distributed data processing

Minimum Qualifications

• PhD, MS or equivalent experience
• Experience in machine learning, deep learning, information retrieval, natural language processing or data mining
• Experience of prompt engineering, fine-tuning, evaluating, and developing data collection/annotation/management tooling for LLMs.
• Proficiency in one of following languages: Python, Go, Java, C++

Preferred Qualifications

• Excellent data analytical skills
• Good interpersonal skills and team player
• PhD preferred

Apple is an equal opportunity employer that is committed to inclusion and diversity, and thus we treat all applicants fairly and equally. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.

About our group:

Seagate Research Group (SRG) conducts research to transform Seagate’s considerable technical expertise, innovation, and manufacturing excellence to develop innovative technologies for the rapidly growing datasphere. 

SRG - Data Trust (DT) Vector focuses on increasing security & privacy capabilities to anchor Seagate as the industry leader of trustworthy storage solutions. 

Currently, the DT team is seeking a candidate to research exciting emerging cryptographical algorithms, protocol and/or security technologies. This position offers a variety of opportunities to prototype, experiment, and benchmark innovative ideas and concepts in projects.  

About the role - you will:

As a Data Trust Security Researcher, you will collaborate with a team of researchers and engineers to explore and evaluate next‑generation security technologies. In this role, you will:

Prototype and evaluate cryptographic algorithms, including Post‑Quantum Cryptography (PQC) and conventional cryptography

Assess and validate security protocols for embedded and resource‑constrained environments

Explore memory‑safe programming languages for secure embedded implementations

Research the evolving threat landscape and identify applicable mitigation techniques

Work with Seagate Research teams on topics such as cryptography, product security, and data security

Conduct performance benchmarking, robustness analysis, and experimental validation of security techniques

Contribute to proof‑of‑concepts and experimental platforms involving cryptography, hardware trust, or secure embedded systems

About you:

We’re Looking for Someone Who Is:

Knowledgeable in cryptography, security standards, and protocols

Knowledgeable with memory‑safe languages

A collaborative team player with a proactive, learning‑oriented mindset

Able to clearly articulate technical concepts to both technical and cross‑functional audiences

Your experience includes:

PHD in Cryptology , mathematics or any relevant fields.

Implementing or designing cryptographic algorithms

Applying or researching Post‑Quantum Cryptography (PQC)

Software development

Working with embedded systems programming and debugging security-related projects an advantage

Experience with biometric security systems is an advantage

Development experience in Linux environments

FPGA development or hardware‑accelerated implementations for cryptography or security projects

About our group:

Seagate Research Group (SRG) conducts research to transform Seagate’s considerable technical expertise, innovation, and manufacturing excellence to develop innovative technologies for the rapidly growing datasphere. 

SRG - Data Trust (DT) Vector focuses on increasing security & privacy capabilities to anchor Seagate as the industry leader of trustworthy storage solutions. 

Currently, the DT team is seeking a candidate to research exciting emerging cryptographical algorithms, protocol and/or security technologies. This position offers a variety of opportunities to prototype, experiment, and benchmark innovative ideas and concepts in projects.  

About the role - you will:

As a Data Trust Security Researcher, you will collaborate with a team of researchers and engineers to explore and evaluate next‑generation security technologies. In this role, you will:

Prototype and evaluate cryptographic algorithms, including Post‑Quantum Cryptography (PQC) and conventional cryptography

Assess and validate security protocols for embedded and resource‑constrained environments

Explore memory‑safe programming languages for secure embedded implementations

Research the evolving threat landscape and identify applicable mitigation techniques

Work with Seagate Research teams on topics such as cryptography, product security, and data security

Conduct performance benchmarking, robustness analysis, and experimental validation of security techniques

Contribute to proof‑of‑concepts and experimental platforms involving cryptography, hardware trust, or secure embedded systems

About you:

We’re Looking for Someone Who Is:

Knowledgeable in cryptography, security standards, and protocols

Knowledgeable with memory‑safe languages

A collaborative team player with a proactive, learning‑oriented mindset

Able to clearly articulate technical concepts to both technical and cross‑functional audiences

Your experience includes:

PHD in Cryptology, mathematics or any relevant fields.

Implementing or designing cryptographic algorithms

Applying or researching Post‑Quantum Cryptography (PQC)

Software development

Working with embedded systems programming and debugging security-related projects an advantage

Experience with biometric security systems is an advantage

Development experience in Linux environments

FPGA development or hardware‑accelerated implementations for cryptography or security projects

Summary

We are seeking an AI/ML Researcher to lead the research and development of large language models (LLMs) solutions. The ideal candidate will have a minimum of 2 years of experience in NLP research and a deep understanding of core LLM components, including LLM modeling, information retrieval, entity-relation extraction, agentic frameworks, and reasoning. The role involves leveraging AI/ML algorithm framework, such as TensorFlow and PyTorch, to develop cutting-edge generative LLM solutions. Responsibilities include designing and conducting scientific experiments, utilizing NLP techniques and LLM core components to develop novel LLM solutions in cloud or on-premises environments. The candidate will also be expected to collaborate with the team, participate in code reviews, architecture discussions, and create comprehensive documentation. The ideal candidate should possess a strong foundation in statistical analysis, machine learning, deep learning, generative AI, and text representation techniques. Additionally, the candidate should have excellent communication skills, a strong work ethic, and a passion for delivering high-quality, innovative solutions.

Responsibilities:

• Leading in designing the research and experiment methodology, specifically in LLM core components.
• Conduct independent research and report experiment results, research findings to stakeholders.
• Collaborate with engineering team in various data engineering tasks, including data collection, preprocessing, quality control, and augmentation, to curate high-quality datasets essential for model training,
• Utilize analytical techniques to extract meaningful insights from large datasets
• Communicating regularly with supervisor and Research leads on scientifical progress, insight and research direction.
• Publishing research papers in reputable journals and conferences is valued, it is not a strict requirement for this role.
• Contribute to other program-related projects.
• Collaborate with engineering team to translate researched technology (low TRL) to engineering (high TRL).
• Candidates applying for senior staff positions are expected to mentor and support team members (or cross-team members) in technical advising.

Requirement:

• Masters or PhD in Computer Science, Computer Engineering, Statistics, Engineering, or related field.
• 2-4 years of experience in research and development, specifically in one or more of the following areas:

1. Natural language processing, specifically in large language model (LLM) core component, e.g., joint entity relation, information retrieval, prompt engineering, reasoning, sentiment analysis, vulnerabilities in LLM, etc.
2. Generative AI, specifically in generating synthetic data.

• Demonstrate an analytical mindset with adept problem-solving skills.
• Keep abreast of the latest advancements in program-related techniques and methodologies,
• Exhibit a strong drive to deliver optimal solutions within tight timelines.
• Strong communication and organizational skills.
• Comprehensive documentation of technical specifications, architectural designs, and best practices.

Summary

This is an applied AI research role. The researcher will design and build non-deterministic analytical tools — grounded in statistical modelling, predictive models, and machine learning — that work across structured and unstructured data. Another part of the role is developing AI agents powered by large language models (LLMs) that can reason over and orchestrate these tools to solve real analytical problems end to end. The researcher is expected to be rigorous with data, curious about intelligent systems, and motivated by seeing their work produce something that actually runs.

Responsibilities

Research & Analysis

• Work with structured datasets to identify patterns, trends, and statistically significant findings that inform research questions and business decisions.
• Apply and adapt predictive models (regression, classification, time series forecasting) and mathematical models to address defined research problems.
• Conduct exploratory data analysis (EDA) to assess data quality, distributions, and feature relevance prior to modelling.
• Design and run statistical experiments, including hypothesis testing, power analysis, and significance testing.
• Validate model performance using appropriate evaluation frameworks and communicate limitations honestly.

AI development

• Study and apply LLM-based agent frameworks to automate and orchestrate research workflows.
• Design and build AI agents that use LLMs as a reasoning engine, with data science models and pipelines exposed as callable tools.
• Integrate agent outputs with structured data — enabling agents to query databases, invoke predictive models, and interpret results.
• Evaluate agent performance: task completion, reasoning coherence, tool-use accuracy, hallucination rate, and failure handling.
• Stay current with the evolving agent landscape and share learnings with the team.

Technical development

• Write clean, well-documented Python code for data processing, feature engineering, model development, and result visualisation.
• Query and manipulate structured data from relational databases using SQL.
• Use core data science libraries including Pandas, NumPy, Scikit-learn, Matplotlib/Seaborn, etc.
• Contribute to shared codebases, following team coding standards and version control practices (KLASS Gitlab).
• Assist in building reproducible data pipelines and experiment tracking workflows.

Collaboration & communication

• Work closely with senior researchers and principal researchers to scope, plan, and deliver project workstreams.
• Contribute to the quarterly and annual research reports, translating technical findings into clear, accessible language.
• Present findings to internal and client-side collaborators, including non-technical audiences.
• Participate in team research reviews, peer code reviews, and knowledge-sharing sessions.

Requirements

Education

• Master’s or PhD – Computer Science, Mathematics, Statistics, Physics, Engineering, Data Science, or a closely related quantitative discipline. (Preferred)
• Bachelor’s Degree – In a relevant quantitative field, with demonstrable hands-on experience in data science (e.g. internships, research projects, competitions, or open-source contributions).
• Fresh Graduates – Encouraged to apply. We value strong fundamentals and intellectual curiosity over years of experience.

Technical skills — essential

• Python programming: proficiency with core data science libraries (Pandas, NumPy, Scikit-learn, SciPy, Matplotlib, Seaborn).
• Data wrangling: handling missing data, outlier detection, feature engineering, and normalisation on structured datasets.
• Mathematical foundations: linear algebra, calculus, and optimisation as applied to machine learning and statistical modelling.
• Working knowledge of modelling families: supervised, unsupervised, and generative models — see the dedicated modelling section below for full detail.

Personal Qualities

1. Research mindsetIntellectually curious across both quantitative and AI domainsRigorous and detail-oriented in analysis and documentationComfortable with ambiguity and iterative problem-solvingHonest about uncertainty — in models and in LLM outputs
2. Working styleClear communicator, written and verbalCollaborative team player in a research environmentSelf-directed with good time managementEager to learn and receive constructive feedback

Experience

0–2 years of professional or research experience

We define experience broadly. Relevant experience includes academic research projects, dissertations with a data science component, internships, industry placements, personal or open-source projects, Kaggle competitions, or research assistant roles. We are more interested in the quality of your analytical thinking than the number of years on your CV.

Job Title: Technology Researcher

Employment Type: Perm Role

Location: Singaporean, Central

About the Role:

We’re looking for someone who is naturally curious, adaptable, and driven to learn. Where you’ll be exploring technologies, analysing markets, and uncovering insights that shape business decisions.

The environment is fast-moving and constantly evolving priorities can shift, and new technologies emerge quickly. Success in this role isn’t just about research skills, but about how quickly you can get up to speed, connect the dots, and adapt your approach when needed.

If you enjoy figuring things out, working through ambiguity, and continuously learning, this role will suit you.

What You’ll Be Doing

• Research and track trends across the IT landscape, including understanding trends and emerging technologies

• Analyse regional markets to understand differences in customer needs, behaviours, and demand drivers

• Evaluate competitor products, features, and positioning to identify gaps and opportunities

What Success Looks Like

• You quickly get up to speed on new technologies, industries, or markets

• You’re able to shift focus and reprioritise as business needs evolve

• You take initiative to explore beyond the brief and surface meaningful insights

What We’re Looking For

• Strong curiosity and interest in understanding technology and digital products

• Adaptable, with the ability to pivot in a fast-changing environment

• Demonstrated willingness to learn, especially in unfamiliar or emerging domains

• Solid analytical and problem-solving skills with a structured approach to research

• Comfortable exploring and evaluating new technologies and digital solutions

• Clear communicator, able to engage stakeholders and present insights effectively

If you don’t meet every requirement but bring strong curiosity, adaptability, and a willingness to learn, we encourage you to apply or send your CV to r.koh@tenthrevolution.com

EA License Number: 11C3017

EA Personnel Number: R21100713