591 Genai Specialist jobs in Singapore

As a lead engineer in AI infrastructure development, you will play a pivotal role in building scalable and efficient systems using cutting-edge deep learning models. Your key responsibilities will include designing, implementing, and optimizing large-scale transformer-based architectures to drive business innovation.

The ideal candidate will have 5+ years of experience in software engineering with a strong focus on deep learning and NLP. They should possess solid software engineering skills, including experience with distributed systems and excellent problem-solving skills. A strong background in LLMs (e.g., GPT, BERT, T5) and frameworks such as PyTorch is also highly desirable.

• Key Responsibilities:
• Design, implement, and optimize large-scale deep learning models focusing on LLM architectures like transformers
• Develop and maintain robust data pipelines for training, fine-tuning, and deploying LLMs at scale
• Collaborate with cross-functional teams to translate cutting-edge AI research into production-ready solutions
• Lead code reviews, mentor junior engineers, and set best practices for software development and ML engineering
• Stay up-to-date with the latest advancements in deep learning and NLP, integrating innovations to enhance model capabilities
• Present technology capabilities and expertise through internal and external communications

Position Summary
To accelerate the adoption of clinical sequencing, Illumina is recruiting a world-class Machine Learning Scientist and Software Engineer to work on the development of novel deep learning algorithms and production-ready software for deciphering the effects of genetic variants in the human genome.
Major aims include modeling the effects of genetic variants on gene function, transcriptional regulation, and diagnosis of pathogenic variants in patients with cancer or rare genetic diseases. A key objective is to develop robust, scalable software implementations of research results and publish these findings in peer-reviewed journals. This will improve the accuracy, throughput, and reproducibility of genome interpretation, thereby removing barriers to the clinical adoption of whole genome sequencing. In addition to strong analytical and software development skills, this position will require initiative, autonomy, and scientific collaboration.
Responsibilities
Contribute to the development of deep learning algorithms for interpreting human genetic data, supporting efforts to identify pathogenic genetic variants using information from clinical phenotypes, protein structures, and genomic data.
Implement, test, and document software modules under the guidance of senior team members, with a focus on reliability, scalability, and efficiency.
Support collaborations with internal and external partners by preparing datasets, running analyses, and contributing to project deliverables.
Assist in preparing research results for internal reports, presentations, and publications, and contribute to integrating methods into software products for the genetics community.
Note: Listed responsibilities are an essential, but not exhaustive, list of usual duties. Changes may occur due to business needs.
Preferred Requirements
Knowledge in deep learning, statistics, bioinformatics, and/or genomics.
Knowledge in full-stack software development and deployment of scientific software.
Familiarity with software development best practices, including version control (e.g., Git), testing frameworks, and CI/CD.
Strong communication skills.
Ability to work in a fast-paced, competitive environment, with a track record of delivering complex scientific projects and publications under tight timelines.
Preferred Experience/Education
BS or MS in computer science, bioinformatics, computational biology, or a related field.
Illumina is an equal opportunity employer committed to providing employment opportunities regardless of sex, race, creed, color, gender, religion, marital status, domestic partner status, age, national origin or ancestry, physical or mental disability, medical condition, sexual orientation, pregnancy, military or veteran status, citizenship status or genetic information. We conduct background checks on applicants whom a conditional offer has been made. The background check process and any decisions will be made in accordance with applicable laws. Illumina prohibits the use of generative AI in the application and interview process. If you require accommodation to complete the application or interview process, please contact
To learn more, visit: The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants. This role is not eligible for visa sponsorship.
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Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of- concepts, and make plans for launching solutions at scale.

The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.

As a Deep Learning Architect, you will

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to product and engineering teams to help define product direction

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

BASIC QUALIFICATIONS

• Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
• 5+ years of experience in designing, building, and/or operating cloud solutions in a production environment
• 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
• 4+ years of hands on experience with Python to build, train, and evaluate models
• 4+ years of technical client engagement experience

PREFERRED QUALIFICATIONS

• Masters or PhD degree in computer science, or related technical, math, or scientific field
• 3+ years experience working with deep learning, machine learning, generative AI, or statistics
• Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker.
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience building cloud solutions with AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Job details

SGP, Singapore

Data Science

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of- concepts, and make plans for launching solutions at scale.

The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.

As a Deep Learning Architect, you will

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to product and engineering teams to help define product direction

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

• Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
• 5+ years of experience in designing, building, and/or operating cloud solutions in a production environment
• 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
• 4+ years of hands on experience with Python to build, train, and evaluate models
• 4+ years of technical client engagement experience

• Masters or PhD degree in computer science, or related technical, math, or scientific field
• 3+ years experience working with deep learning, machine learning, generative AI, or statistics
• Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker.
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience building cloud solutions with AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of- concepts, and make plans for launching solutions at scale.

The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.

As a Deep Learning Architect, you will

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to product and engineering teams to help define product direction

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

• Bachelor's degree in Computer Science or a related field
• 5+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
• Experience managing and deploying ML products
• 4+ years of building machine learning models for business application experience
• 5+ years of leading and delivering enterprise-level IT engagements experience

• Master's degree in computer science, computer engineering, or related field, or PhD
• 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
• 8+ years of leading development of applications backed by AWS services or using other cloud based technologies and services experience
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience architecting/operating solutions built on AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of- concepts, and make plans for launching solutions at scale.

The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.

As a Deep Learning Architect, you will

• Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
• Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
• Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
• Provide customer and market feedback to product and engineering teams to help define product direction

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic qualifications

• Bachelor's degree in Computer Science or a related field
• 5+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
• Experience managing and deploying ML products
• 4+ years of building machine learning models for business application experience
• 5+ years of leading and delivering enterprise-level IT engagements experience

Preferred qualifications

• Master's degree in computer science, computer engineering, or related field, or PhD
• 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
• 8+ years of leading development of applications backed by AWS services or using other cloud based technologies and services experience
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
• Experience architecting/operating solutions built on AWS

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of- concepts, and make plans for launching solutions at scale.

The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.

You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.

As a Deep Learning Architect, you will

- Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
- Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
- Provide customer and market feedback to product and engineering teams to help define product direction



About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

- Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- 5+ years of experience in designing, building, and/or operating cloud solutions in a production environment
- 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)
- 4+ years of hands on experience with Python to build, train, and evaluate models
- 4+ years of technical client engagement experience

- Masters or PhD degree in computer science, or related technical, math, or scientific field
- 3+ years experience working with deep learning, machine learning, generative AI, or statistics
- Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker.
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience building cloud solutions with AWS