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Senior Staff Bioinformatics Scientist (AI-guided protein engineering) at Illumina Canada Inc. · Katori

Asks for

The ad says“Significant experience leading computational biology, protein engineering, AI/ML, screening analytics, or scientific data infrastructure efforts”
The ad says“Understanding of AI/ML methods and practical experience in adopting AI/ML-driven protein-design models.”
The ad says“Strong fundamentals in statistical modelling, algorithm design, data analysis, and/or visualization methods.”
The ad says“Solid programming skills in at least one of the major programming languages (e.g., C/C++, Python, R).”
The ad says“Significant experience leading computational biology, protein engineering, AI/ML, screening analytics, or scientific data infrastructure efforts”
The ad says“Strong fundamentals in statistical modelling, algorithm design, data analysis, and/or visualization methods.”
The ad says“Demonstrated ability to design data structures or analytical systems that support reproducible analysis, model training, and cross-project learning.”
The ad says“In-depth knowledge of protein sequence or structure modelling, protein-ligand interaction predictions and/or molecular simulations.”
The ad says“Significant experience leading computational biology, protein engineering, AI/ML, screening analytics, or scientific data infrastructure efforts”
The ad says“In-depth knowledge of protein sequence or structure modelling, protein-ligand interaction predictions and/or molecular simulations.”
The ad says“In-depth knowledge of protein sequence or structure modelling, protein-ligand interaction predictions and/or molecular simulations.”
The ad says“Solid programming skills in at least one of the major programming languages (e.g., C/C++, Python, R).”
The ad says“Solid programming skills in at least one of the major programming languages (e.g., C/C++, Python, R).”
The ad says“Significant experience leading computational biology, protein engineering, AI/ML, screening analytics, or scientific data infrastructure efforts”
The ad says“Strong fundamentals in statistical modelling, algorithm design, data analysis, and/or visualization methods.”
The ad says“Strong fundamentals in statistical modelling, algorithm design, data analysis, and/or visualization methods.”
The ad says“Wet-lab experience in high-throughput or mid-throughput screening and/or biochemical assay designs.”

Values

The ad says“Knowledge of biochemistry, enzymology, and/or molecular biology.”
The ad says“Broad knowledge of bioinformatics, genomics, and/or proteomics database, tools, and/or algorithms.”
The ad says“Experience with structure prediction, protein-ligand or enzyme-substrate modeling, molecular dynamics, docking, or biophysical analysis (e.g. Protein MPNN, RFdiffusion, Boltz, Alphafold)”
The ad says“Experience with structure prediction, protein-ligand or enzyme-substrate modeling, molecular dynamics, docking, or biophysical analysis (e.g. Protein MPNN, RFdiffusion, Boltz, Alphafold)”
The ad says“Knowledge of biochemistry, enzymology, and/or molecular biology.”
The ad says“Experience with foundational AI/ML models and protein language models for protein engineering, including generative protein design, zero-shot variant scoring, supervised learning, model-guided library design, denoising and uncertainty-aware learning, and multi-parameter optimization of protein properties”
The ad says“Broad knowledge of bioinformatics, genomics, and/or proteomics database, tools, and/or algorithms.”
The ad says“Knowledge of best software development practices and code version control, e.g. Git.”
The ad says“Experience with high-performance computing, job schedulers, and/or GPU computing.”
The ad says“Experience with high-performance computing, job schedulers, and/or GPU computing.”
The ad says“Deep learning frameworks such as PyTorch, TensorFlow, or JAX”
The ad says“Knowledge of biochemistry, enzymology, and/or molecular biology.”
The ad says“Experience with structure prediction, protein-ligand or enzyme-substrate modeling, molecular dynamics, docking, or biophysical analysis (e.g. Protein MPNN, RFdiffusion, Boltz, Alphafold)”
The ad says“Familiarity with next generation sequencing technologies, tools, and/or workflows.”
The ad says“Experience with foundational AI/ML models and protein language models for protein engineering, including generative protein design, zero-shot variant scoring, supervised learning, model-guided library design, denoising and uncertainty-aware learning, and multi-parameter optimization of protein properties”
The ad says“Broad knowledge of bioinformatics, genomics, and/or proteomics database, tools, and/or algorithms.”
The ad says“Deep learning frameworks such as PyTorch, TensorFlow, or JAX”
The ad says“Knowledge of UNIX environment and shell scripting.”
The ad says“Experience with structure prediction, protein-ligand or enzyme-substrate modeling, molecular dynamics, docking, or biophysical analysis (e.g. Protein MPNN, RFdiffusion, Boltz, Alphafold)”
The ad says“Deep learning frameworks such as PyTorch, TensorFlow, or JAX”
The ad says“Knowledge of UNIX environment and shell scripting.”

What if the work you did every day could impact the lives of people you know? Or all of humanity?

At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients.

Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible.

Why us

Illumina is the global leader in Next Generation Sequencing (NGS) technology. Through relentless innovation, Illumina has reduced the cost of sequencing a human genome from hundreds of thousands of dollars to below $200. The drastic cost reduction has moved NGS from the laboratory to the clinic, with wide-ranging impact from cancer diagnostics to genetic testing. We invite you to join us in our effort to improve human health by unlocking the power of the genome.

Position summary

We are seeking a Senior Staff Scientist to help build computational tools and data foundation for our protein engineering group across global enzyme engineering programs. This role will connect data structures for high-throughput and mid-throughput screening, participate in method development and evaluation, and help establish semi-closed-loop and closed-loop design-build-test-learn workflows.

The successful candidate will provide senior technical leadership at the interface of protein engineering, AI/ML design, screening data systems, automation, and experimental execution. This scientist will define how screening results become reusable data assets as well as how computational methods are benchmarked and adopted.

The role is based in Singapore. This is an exciting opportunity to be a part of Illumina’s continued growth.

Responsibilities include, but are not limited to:

Build reusable data foundations for protein engineering. Define data structures, metadata standards, variant lineage, assay context, controls, replicate handling, uncertainty, and negative data capture across high- and mid-throughput screening workflows.
Enable model-guided enzyme engineering. Develop and evaluate computational workflows that connect sequence, structure, assay, and screening datasets to AI/ML models, design rationale, variant prioritization, and next-round library design.
Benchmark computational and AI methods. Assess internal pipelines, open-source methods, commercial protein design platforms, and emerging scientific agents using retrospective and prospective performance metrics relevant to enzyme engineering programs.
Deliver practical tools for project teams. Create reusable scripts, templates, dashboards, lightweight applications, and analysis pipelines that help experimental and computational teams run routine analyses and interpret recommendations efficiently.
Advance closed-loop DBTL workflows. Help establish semi-closed-loop and closed-loop design-build-test-learn systems in which experimental results are captured, analyzed, modeled, reviewed, and converted into actionable design recommendations.
Partner across global engineering programs. Work closely with experimental scientists, automation teams, informatics, software engineering, data engineering, chemists, biophysicists, and platform teams to ensure computational workflows align with assay throughput, operational constraints, and program goals.

All listed tasks and responsibilities are deemed as essential functions to this position; however, business conditions may require reasonable accommodations for additional task and responsibilities.

Education, Experience & Attributes required:

Ph.D. in computational chemistry, computational biology, bioinformatics, computer science or related fields, or equivalent work & educational experience.
Significant experience leading computational biology, protein engineering, AI/ML, screening analytics, or scientific data infrastructure efforts
Deep experience applying computational or data-driven methods to protein engineering, enzyme engineering, directed evolution, assay analysis, or related biological design problems.
Demonstrated ability to design data structures or analytical systems that support reproducible analysis, model training, and cross-project learning.
Wet-lab experience in high-throughput or mid-throughput screening and/or biochemical assay designs.
Solid programming skills in at least one of the major programming languages (e.g., C/C++, Python, R).
In-depth knowledge of protein sequence or structure modelling, protein-ligand interaction predictions and/or molecular simulations.
Understanding of AI/ML methods and practical experience in adopting AI/ML-driven protein-design models.
Strong fundamentals in statistical modelling, algorithm design, data analysis, and/or visualization methods.
Excellent verbal and written communication skills.
Collaborative, open and self-aware, team player, and able to rapidly integrate into cross functional teams.
Highly motivated individual with proven ability in thinking innovatively and the proven track record of productive research and development.

Strong applicants with lesser experience will be considered for a position commensurate with the experience.

Preferred experiences and attributes

Experience with foundational AI/ML models and protein language models for protein engineering, including generative protein design, zero-shot variant scoring, supervised learning, model-guided library design, denoising and uncertainty-aware learning, and multi-parameter optimization of protein properties

Experience with structure prediction, protein-ligand or enzyme-substrate modeling, molecular dynamics, docking, or biophysical analysis (e.g. Protein MPNN, RFdiffusion, Boltz, Alphafold)

Experience developing data standards, assay schemas, dashboards, or lightweight tools for experimental scientists.

Experience with developing AI agents and agentic workflows for method and application development, and automatic execution and optimization of computational pipelines,
Deep learning frameworks such as PyTorch, TensorFlow, or JAX
Large-scale biological data analysis using cloud or high-performance computing environments
Practical experience with AI/ML model development for protein design.
Experience with experiments within protein engineering, e.g. directed-evolution, high-throughput screening.
Experience in using one or more commonly used molecular modelling software, e.g. Rosetta.
Knowledge of best software development practices and code version control, e.g. Git.
Knowledge of UNIX environment and shell scripting.
Experience with high-performance computing, job schedulers, and/or GPU computing.
Broad knowledge of bioinformatics, genomics, and/or proteomics database, tools, and/or algorithms.
Knowledge of biochemistry, enzymology, and/or molecular biology.
Familiarity with next generation sequencing technologies, tools, and/or workflows.

We are a company deeply rooted in belonging, promoting an inclusive environment where employees feel valued and empowered to contribute to our mission. Built on a strong foundation, Illumina has always prioritized openness, collaboration, and seeking alternative perspectives to propel innovation in genomics. We are proud to confirm a zero-net gap in pay, regardless of gender, ethnicity, or race. We also have several Employee Resource Groups (ERG) that deliver career development experiences, increase cultural awareness, and offer opportunities to engage in social responsibility. We are proud to be an equal opportunity employer committed to providing employment opportunity 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, and genetic information. Illumina conducts background checks on applicants for whom a conditional offer of employment has been made. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable local, state, and federal laws. Background check results may potentially result in the withdrawal of a conditional offer of employment. The background check process and any decisions made as a result shall be made in accordance with all applicable local, state, and federal laws. Illumina prohibits the use of generative artificial intelligence (AI) in the application and interview process. If you require accommodation to complete the application or interview process, please contact accommodations@illumina.com. To learn more, visit: https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf. The position will be posted until a final candidate is selected or the requisition has a sufficient number of qualified applicants.