TN Visa Principal Scientist Jobs
Principal Scientist roles qualify for TN visa sponsorship under the USMCA's Scientist category, covering research positions in biology, chemistry, and related fields. Canadian professionals can enter at the border with employer documentation; Mexican nationals apply at a U.S. consulate. Roles must require at least a bachelor's degree in a relevant scientific discipline.
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About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
Position Overview
We are seeking an accomplished scientific leader in AI-enabled computational biology to establish and advance next-generation immunogenicity and translational immunology capabilities across biologics discovery and development. The successful candidate will serve as a discipline expert and strategic partner, combining machine learning, protein language models, structural modeling, systems immunology, and computational biology to predict, understand, and mitigate anti-drug antibody (ADA) responses and other immune-mediated liabilities across therapeutic proteins, multispecific antibodies, antibody-drug conjugates, gene therapies, and novel modalities.
This individual will define scientific strategy, lead high-impact cross-functional programs, build fit-for-purpose computational capabilities, and translate complex analyses into clear recommendations for project teams, governance bodies, and senior leaders. The role includes direct people leadership and accountability for developing an effective, collaborative, and scientifically excellent team.
Key Responsibilities
Scientific Strategy and Functional Leadership
- Develop and deliver the computational immunogenicity strategy in alignment with Development Sciences priorities and key scientific objectives.
- Serve as the discipline expert and primary contact for AI/ML-enabled immunogenicity, protein engineering, and translational modeling.
- Identify emerging scientific and technology trends, assess their relevance, and translate them into short- and long-term functional objectives.
- Create, champion, and implement innovative approaches that improve candidate selection, risk mitigation, and transition success.
AI/ML-Based Immunogenicity and Protein Modeling
- Lead development and deployment of predictive models for preclinical and clinical immunogenicity risk assessment.
- Integrate ADA incidence, PK/PD, HLA, sequence, structure, developability, assay, and patient-level data using machine learning and deep learning approaches.
- Apply protein language models, foundation models, transformers, generative AI, and physics-informed modeling to identify immunogenicity drivers, biomarkers, and design opportunities.
- Develop or guide methods to predict ADA incidence and persistence, T-cell epitope content, HLA-associated risk, patient susceptibility, and drug-like properties of biologics.
Systems Immunology, Multi-Omics, and Translational Modeling
- Integrate transcriptomic, proteomic, single-cell, spatial biology, flow cytometry, bioanalytical, and clinical datasets to characterize immune responses to biologics.
- Build computational frameworks linking in vitro and ex vivo assays, nonclinical observations, molecular mechanisms, and clinical ADA or neutralizing-antibody outcomes.
- Identify biomarkers associated with immune activation, tolerance, and ADA development, and use findings to inform translational and clinical strategies.
Generative AI, Knowledge Integration, and Data Platforms
- Lead development of PLM- and LLM-enabled tools for scientific knowledge mining, hypothesis generation, and immunogenicity risk assessment.
- Guide retrieval-augmented generation and agentic workflows that use scientific literature, historical studies, internal reports, and regulatory guidance.
- Establish integrated, traceable immunogenicity data assets and scalable data pipelines spanning discovery, nonclinical, and clinical development.
- Ensure analytical approaches are reproducible, scientifically defensible, appropriately documented, and fit for their intended use.
Cross-Functional Influence and Communication
- Collaborate with experts across Discovery, Protein Sciences, Bioanalysis, Clinical, Regulatory, Toxicology, Data Science, and other Development Sciences functions.
- Communicate complex scientific concepts, model performance, limitations, and recommendations clearly to technical and non-technical audiences.
- Present scientific strategies and results to project teams, functional leadership, governance committees, senior management, and internal or external partners.
- Build strong working relationships, reconcile differing technical perspectives, and influence decisions through evidence-based recommendations.
People Leadership and Talent Development
- Manage, mentor, and develop a team of computational scientists and/or computational protein engineers; set clear priorities and maintain accountability for high-quality delivery.
- Provide technical guidance, performance coaching, career development, and timely feedback to direct reports.
- Create an inclusive, collaborative environment that encourages scientific rigor, innovation, knowledge sharing, and continuous learning.
- Assess capability needs and help build the talent, partnerships, and operating model required to achieve functional goals.
Qualifications
Required Qualifications
- Ph.D. in computational biology, computational structural biology, bioinformatics, biomedical informatics, computer science, data science, biophysics, or a related scientific field, with typically 8 or more years of related work experience; or a Master’s degree with typically 14 or more years.
- Demonstrated discipline expertise in computational protein science, biologics discovery or development, AI/ML, and predictive modeling.
- Proven ability to define scientific strategy, lead complex multidisciplinary programs, and deliver innovative computational capabilities with measurable scientific or product impact.
- Demonstrated people-management experience, including leading scientific teams, setting priorities, coaching employees, and supporting performance and career development.
- Exceptional written, verbal, and presentation skills, with the ability to communicate clearly and persuasively to scientific, non-scientific, and senior-leadership audiences.
- Strong record of collaboration and influence across diverse internal and external groups.
- Experience with HLA binding prediction, T-cell epitope prediction, MHC-II modeling, single-cell analysis, knowledge graphs, causal AI, RAG systems, or biomedical language models.
- Experience handling, curating, integrating, and governing large experimental, biological, clinical, structural, or multi-omics datasets.
- Experience developing and maintaining reproducible data pipelines, automated workflows, and deployable computational tools.
- Demonstrated understanding of physical principles governing protein structure, folding, binding, developability, and molecular recognition.
Scientific and Technical Expertise
- Protein language models, generative protein design, structural modeling, and computational antibody engineering.
- Biologics developability, property prediction, sequence and structure optimization, and translational decision support.
- Immunology, adaptive immune responses, ADA and neutralizing-antibody biology, immune tolerance, and translational medicine.
- Proficiency in Python and relevant scientific computing, data science, and machine-learning frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost.
- Cloud or scalable computing environments such as AWS, Azure, Databricks, or Snowflake, and effective scientific data visualization.
Preferred Qualifications
- Experience with immunogenicity risk assessment, ADA data interpretation, and relevant FDA or EMA guidance.
- Experience converting computational prototypes into tools that are adopted by research or development teams.
- Publication, patent, invited-presentation, or other record demonstrating scientific innovation and external or internal recognition.
- Experience building collaborations across computational, experimental, translational, and clinical disciplines.
Critical Success Factors
- Strategic scientific leadership paired with hands-on technical depth.
- Innovation that produces practical, trusted, and scalable solutions for biologics development.
- Clear, concise, and influential communication across levels and disciplines.
- Effective people leadership, talent development, and team accountability.
- Sound scientific judgment, early risk assessment, and transparent communication of model limitations.
- Ability to operate effectively in a collaborative, fast-paced, and goal-driven environment.
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
Company Description
About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
Position Overview
We are seeking an accomplished scientific leader in AI-enabled computational biology to establish and advance next-generation immunogenicity and translational immunology capabilities across biologics discovery and development. The successful candidate will serve as a discipline expert and strategic partner, combining machine learning, protein language models, structural modeling, systems immunology, and computational biology to predict, understand, and mitigate anti-drug antibody (ADA) responses and other immune-mediated liabilities across therapeutic proteins, multispecific antibodies, antibody-drug conjugates, gene therapies, and novel modalities.
This individual will define scientific strategy, lead high-impact cross-functional programs, build fit-for-purpose computational capabilities, and translate complex analyses into clear recommendations for project teams, governance bodies, and senior leaders. The role includes direct people leadership and accountability for developing an effective, collaborative, and scientifically excellent team.
Key Responsibilities
Scientific Strategy and Functional Leadership
- Develop and deliver the computational immunogenicity strategy in alignment with Development Sciences priorities and key scientific objectives.
- Serve as the discipline expert and primary contact for AI/ML-enabled immunogenicity, protein engineering, and translational modeling.
- Identify emerging scientific and technology trends, assess their relevance, and translate them into short- and long-term functional objectives.
- Create, champion, and implement innovative approaches that improve candidate selection, risk mitigation, and transition success.
AI/ML-Based Immunogenicity and Protein Modeling
- Lead development and deployment of predictive models for preclinical and clinical immunogenicity risk assessment.
- Integrate ADA incidence, PK/PD, HLA, sequence, structure, developability, assay, and patient-level data using machine learning and deep learning approaches.
- Apply protein language models, foundation models, transformers, generative AI, and physics-informed modeling to identify immunogenicity drivers, biomarkers, and design opportunities.
- Develop or guide methods to predict ADA incidence and persistence, T-cell epitope content, HLA-associated risk, patient susceptibility, and drug-like properties of biologics.
Systems Immunology, Multi-Omics, and Translational Modeling
- Integrate transcriptomic, proteomic, single-cell, spatial biology, flow cytometry, bioanalytical, and clinical datasets to characterize immune responses to biologics.
- Build computational frameworks linking in vitro and ex vivo assays, nonclinical observations, molecular mechanisms, and clinical ADA or neutralizing-antibody outcomes.
- Identify biomarkers associated with immune activation, tolerance, and ADA development, and use findings to inform translational and clinical strategies.
Generative AI, Knowledge Integration, and Data Platforms
- Lead development of PLM- and LLM-enabled tools for scientific knowledge mining, hypothesis generation, and immunogenicity risk assessment.
- Guide retrieval-augmented generation and agentic workflows that use scientific literature, historical studies, internal reports, and regulatory guidance.
- Establish integrated, traceable immunogenicity data assets and scalable data pipelines spanning discovery, nonclinical, and clinical development.
- Ensure analytical approaches are reproducible, scientifically defensible, appropriately documented, and fit for their intended use.
Cross-Functional Influence and Communication
- Collaborate with experts across Discovery, Protein Sciences, Bioanalysis, Clinical, Regulatory, Toxicology, Data Science, and other Development Sciences functions.
- Communicate complex scientific concepts, model performance, limitations, and recommendations clearly to technical and non-technical audiences.
- Present scientific strategies and results to project teams, functional leadership, governance committees, senior management, and internal or external partners.
- Build strong working relationships, reconcile differing technical perspectives, and influence decisions through evidence-based recommendations.
People Leadership and Talent Development
- Manage, mentor, and develop a team of computational scientists and/or computational protein engineers; set clear priorities and maintain accountability for high-quality delivery.
- Provide technical guidance, performance coaching, career development, and timely feedback to direct reports.
- Create an inclusive, collaborative environment that encourages scientific rigor, innovation, knowledge sharing, and continuous learning.
- Assess capability needs and help build the talent, partnerships, and operating model required to achieve functional goals.
Qualifications
Required Qualifications
- Ph.D. in computational biology, computational structural biology, bioinformatics, biomedical informatics, computer science, data science, biophysics, or a related scientific field, with typically 8 or more years of related work experience; or a Master’s degree with typically 14 or more years.
- Demonstrated discipline expertise in computational protein science, biologics discovery or development, AI/ML, and predictive modeling.
- Proven ability to define scientific strategy, lead complex multidisciplinary programs, and deliver innovative computational capabilities with measurable scientific or product impact.
- Demonstrated people-management experience, including leading scientific teams, setting priorities, coaching employees, and supporting performance and career development.
- Exceptional written, verbal, and presentation skills, with the ability to communicate clearly and persuasively to scientific, non-scientific, and senior-leadership audiences.
- Strong record of collaboration and influence across diverse internal and external groups.
- Experience with HLA binding prediction, T-cell epitope prediction, MHC-II modeling, single-cell analysis, knowledge graphs, causal AI, RAG systems, or biomedical language models.
- Experience handling, curating, integrating, and governing large experimental, biological, clinical, structural, or multi-omics datasets.
- Experience developing and maintaining reproducible data pipelines, automated workflows, and deployable computational tools.
- Demonstrated understanding of physical principles governing protein structure, folding, binding, developability, and molecular recognition.
Scientific and Technical Expertise
- Protein language models, generative protein design, structural modeling, and computational antibody engineering.
- Biologics developability, property prediction, sequence and structure optimization, and translational decision support.
- Immunology, adaptive immune responses, ADA and neutralizing-antibody biology, immune tolerance, and translational medicine.
- Proficiency in Python and relevant scientific computing, data science, and machine-learning frameworks such as PyTorch, TensorFlow, scikit-learn, or XGBoost.
- Cloud or scalable computing environments such as AWS, Azure, Databricks, or Snowflake, and effective scientific data visualization.
Preferred Qualifications
- Experience with immunogenicity risk assessment, ADA data interpretation, and relevant FDA or EMA guidance.
- Experience converting computational prototypes into tools that are adopted by research or development teams.
- Publication, patent, invited-presentation, or other record demonstrating scientific innovation and external or internal recognition.
- Experience building collaborations across computational, experimental, translational, and clinical disciplines.
Critical Success Factors
- Strategic scientific leadership paired with hands-on technical depth.
- Innovation that produces practical, trusted, and scalable solutions for biologics development.
- Clear, concise, and influential communication across levels and disciplines.
- Effective people leadership, talent development, and team accountability.
- Sound scientific judgment, early risk assessment, and transparent communication of model limitations.
- Ability to operate effectively in a collaborative, fast-paced, and goal-driven environment.
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
See all 32+ TN Visa Principal Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new TN Visa Principal Scientist Jobs.
Get Access To All JobsTips for Finding TN Visa Sponsorship as a Principal Scientist
Match your credentials to the Scientist category
TN visa's Scientist category covers specific disciplines: biology, chemistry, astronomy, physics, and related fields. Confirm your degree is in one of these recognized disciplines before applying, since a general 'research' background won't satisfy the category definition.
Target employers with active government contract work
Principal Scientist roles at federal contractors, national laboratories, and pharmaceutical companies are structured around credentialed research functions, making TN qualification documentation straightforward. These employers already understand specialty occupation requirements and generate fewer sponsorship objections.
Search TN-eligible roles at sponsors with visa experience
Use Migrate Mate to filter Principal Scientist openings by employers with recent visa filings. This narrows your search to companies experienced with work visa sponsorship and helps you focus on roles where the employer has demonstrated capability to support visa candidates through their sponsorship history.
Request the support letter before accepting an offer
The TN support letter must describe your specific research duties, required qualifications, and how the role fits the Scientist category. Ask the hiring team to draft this during offer negotiation, not after, so USCIS or CBP adjudication doesn't delay your start date.
Prepare a degree equivalency analysis for interdisciplinary roles
If your doctorate is in a hybrid field like computational biology or environmental chemistry, USCIS may scrutinize whether it maps cleanly to a listed TN discipline. A brief written equivalency analysis tied to your transcripts strengthens the petition and preempts requests for evidence.
Understand the Mexican national consular process differs from Canadian
Mexican nationals must schedule a consular appointment and obtain the TN visa stamp before entering the U.S. to work, unlike Canadians who can present documentation directly at a port of entry. Build four to eight weeks into your start date timeline to account for consulate scheduling.
Principal Scientist TN Visa: Frequently Asked Questions
Does a Principal Scientist role qualify for TN visa status?
Yes, if your role falls within a recognized scientific discipline such as biology, chemistry, physics, or a closely related field and requires at least a bachelor's degree in that discipline. The TN Scientist category is specific about qualifying disciplines, so your job duties and degree must both align with the occupational requirements for TN classification, not just a general research function.
How does TN compare to H-1B for Principal Scientist positions?
TN has no annual cap and no lottery for Canadian nationals, so you can start the process as soon as you have a qualifying job offer. H-1B visa is subject to an annual lottery with limited slots, meaning even a well-qualified candidate may wait years for selection. For Mexican nationals, TN has a separate numerical allocation but still avoids the H-1B lottery entirely.
Where can I find Principal Scientist jobs with confirmed TN visa sponsorship?
Migrate Mate lets you filter Principal Scientist roles by employers with recent visa filings, so you're not guessing which companies have experience supporting work visas. Most standard job searches don't surface sponsorship experience at all, which costs candidates weeks of outreach on roles that won't move forward.
Can I switch employers while on TN status as a Principal Scientist?
Yes, but TN status is employer-specific. You'll need a new TN petition or border crossing documentation tied to your new employer before your start date with them. Canadian nationals can typically handle this at a port of entry; Mexican nationals will need to return to a consulate for a new visa stamp tied to the new employer.
What documentation does my employer need to provide for my TN petition?
Your employer must provide a signed support letter on company letterhead that details your job title, a description of your research duties, the scientific discipline your role falls under, your required qualifications, your anticipated start date, and confirmation that the position is full-time. This letter is the primary adjudication document, so vague or generic language about your research function is one of the most common reasons for TN denials at the border.