TN Visa Applied Scientist Jobs
Applied Scientist roles qualify for TN visa sponsorship under the USMCA's Scientific Technician/Technologist and related scientific categories. Canadian citizens can apply at any port of entry without a cap; Mexican citizens require a consular appointment. Employers provide a support letter documenting the role, your qualifications, and anticipated duration of employment.
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You’re joining Core AI, the team at the forefront of redefining how software is built and experienced. We create the foundational platforms, services, and developer experiences that power next-generation applications using Generative AI, enabling developers and enterprises to unlock the full potential of AI to build intelligent, adaptive, and transformative software.
You will be a technical contributor driving the applied science foundation for observability in AI agents and multi-agent systems running at scale. This role focuses on understanding how intelligent agents behave in production—their quality, safety, reliability, cost, and evolution over time. You will develop and apply scientific methods, evaluation frameworks, and measurement systems that help teams understand, benchmark, diagnose, and safely improve agent-based systems with confidence.
AI agents introduce fundamentally new observability challenges: non-deterministic execution, tool- and model-driven decision paths, emergent multi-agent behaviors, and quality signals that go far beyond traditional uptime metrics.
We are hiring multiple Senior and Principal Applied Scientists who will operate at the intersection of agent architecture, telemetry, evaluation science, and responsible AI, shaping how Microsoft measures and improves observable AI systems.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
Responsibilities
- Develop evaluation and measurement frameworks for single-agent and multi-agent systems, spanning quality, safety, reliability, cost, and behavioral consistency.
- Design methodologies that connect offline evals, online signals, and production telemetry to explain how prompt, tool, model, or orchestration changes affect real-world agent performance.
- Define scientifically grounded quality signals and benchmarks for agent systems, including task success, tool-use effectiveness, plan quality, failure modes, coordination quality, and user-perceived outcomes.
- Build models and analysis techniques that help detect regressions, identify root causes, and characterize agent behavior across diverse workflows and environments.
- Advance observability for AI systems through new approaches to trace analysis, agent health modeling, behavioral clustering, anomaly detection, and multi-agent coordination analysis.
- Partner with engineering teams to operationalize evaluation and observability methods in production systems, enabling safe iteration through staged rollouts, experimentation, A/B testing, and automated regression detection.
- Contribute to instrumentation and semantic standards for agent observability, helping make agent execution more explainable, diagnosable, and comparable across systems.
- Collaborate deeply with product and platform teams across Foundry, Azure Monitor, and agent runtimes to shape end-to-end experiences for evaluation, benchmarking, monitoring, and investigation.
- Act as a technical leader by setting scientific direction, driving research-informed product decisions, mentoring others, and raising the technical bar across the organization.
Technical Focus Areas
- Evaluation science for agent and multi-agent systems: offline, online, and continuous evals; benchmark design; synthetic data; task success measurement
- Agent and multi-agent architectures: planners, tool use, memory, orchestration, and coordination patterns
- Applied machine learning and statistical methods for behavioral analysis, anomaly detection, experimentation, and regression detection
- Observability data for AI systems: traces, logs, metrics, evaluations, and cost/performance signals
- Safety and responsible AI signals: policy compliance, risk detection, auditability, and safe logging
- Benchmarking and experimentation for agent systems, including A/B tests, canaries, and staged rollouts
- Explainability and diagnosis for complex agent workflows and model-driven decision paths
Qualifications
Required Qualifications
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
Other Requirements
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
- Experience designing evaluation methodologies, experiments, or measurement systems for complex intelligent or distributed systems
- Experience analyzing large-scale production or experimental data to derive actionable insights and drive product or system improvements
- Strong coding and prototyping skills in Python or similar languages, with the ability to work closely with engineering teams on production-facing systems
- Demonstrated ability to lead cross-team technical direction through scientific depth, influence, and strong problem framing
- Advanced degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field
- Experience building or evaluating LLM- or agent-based systems in production
- Familiarity with agent frameworks such as LangChain, LangGraph, OpenAI SDK, or equivalent orchestration frameworks
- Experience with evaluation frameworks for AI systems, including benchmarking, regression analysis, and human-in-the-loop assessment
- Experience with observability systems, telemetry analysis, or distributed tracing data in large-scale environments
- Background in AI safety, guardrails, and responsible AI measurement
- Experience with experimentation platforms, causal inference, or statistical methods for product and model evaluation
- Experience working with cloud-scale monitoring platforms such as Azure Monitor / Application Insights or equivalent
Compensation
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
Overview
You’re joining Core AI, the team at the forefront of redefining how software is built and experienced. We create the foundational platforms, services, and developer experiences that power next-generation applications using Generative AI, enabling developers and enterprises to unlock the full potential of AI to build intelligent, adaptive, and transformative software.
You will be a technical contributor driving the applied science foundation for observability in AI agents and multi-agent systems running at scale. This role focuses on understanding how intelligent agents behave in production—their quality, safety, reliability, cost, and evolution over time. You will develop and apply scientific methods, evaluation frameworks, and measurement systems that help teams understand, benchmark, diagnose, and safely improve agent-based systems with confidence.
AI agents introduce fundamentally new observability challenges: non-deterministic execution, tool- and model-driven decision paths, emergent multi-agent behaviors, and quality signals that go far beyond traditional uptime metrics.
We are hiring multiple Senior and Principal Applied Scientists who will operate at the intersection of agent architecture, telemetry, evaluation science, and responsible AI, shaping how Microsoft measures and improves observable AI systems.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
Responsibilities
- Develop evaluation and measurement frameworks for single-agent and multi-agent systems, spanning quality, safety, reliability, cost, and behavioral consistency.
- Design methodologies that connect offline evals, online signals, and production telemetry to explain how prompt, tool, model, or orchestration changes affect real-world agent performance.
- Define scientifically grounded quality signals and benchmarks for agent systems, including task success, tool-use effectiveness, plan quality, failure modes, coordination quality, and user-perceived outcomes.
- Build models and analysis techniques that help detect regressions, identify root causes, and characterize agent behavior across diverse workflows and environments.
- Advance observability for AI systems through new approaches to trace analysis, agent health modeling, behavioral clustering, anomaly detection, and multi-agent coordination analysis.
- Partner with engineering teams to operationalize evaluation and observability methods in production systems, enabling safe iteration through staged rollouts, experimentation, A/B testing, and automated regression detection.
- Contribute to instrumentation and semantic standards for agent observability, helping make agent execution more explainable, diagnosable, and comparable across systems.
- Collaborate deeply with product and platform teams across Foundry, Azure Monitor, and agent runtimes to shape end-to-end experiences for evaluation, benchmarking, monitoring, and investigation.
- Act as a technical leader by setting scientific direction, driving research-informed product decisions, mentoring others, and raising the technical bar across the organization.
Technical Focus Areas
- Evaluation science for agent and multi-agent systems: offline, online, and continuous evals; benchmark design; synthetic data; task success measurement
- Agent and multi-agent architectures: planners, tool use, memory, orchestration, and coordination patterns
- Applied machine learning and statistical methods for behavioral analysis, anomaly detection, experimentation, and regression detection
- Observability data for AI systems: traces, logs, metrics, evaluations, and cost/performance signals
- Safety and responsible AI signals: policy compliance, risk detection, auditability, and safe logging
- Benchmarking and experimentation for agent systems, including A/B tests, canaries, and staged rollouts
- Explainability and diagnosis for complex agent workflows and model-driven decision paths
Qualifications
Required Qualifications
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
Other Requirements
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
Preferred Qualifications
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience.
- Experience designing evaluation methodologies, experiments, or measurement systems for complex intelligent or distributed systems
- Experience analyzing large-scale production or experimental data to derive actionable insights and drive product or system improvements
- Strong coding and prototyping skills in Python or similar languages, with the ability to work closely with engineering teams on production-facing systems
- Demonstrated ability to lead cross-team technical direction through scientific depth, influence, and strong problem framing
- Advanced degree in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field
- Experience building or evaluating LLM- or agent-based systems in production
- Familiarity with agent frameworks such as LangChain, LangGraph, OpenAI SDK, or equivalent orchestration frameworks
- Experience with evaluation frameworks for AI systems, including benchmarking, regression analysis, and human-in-the-loop assessment
- Experience with observability systems, telemetry analysis, or distributed tracing data in large-scale environments
- Background in AI safety, guardrails, and responsible AI measurement
- Experience with experimentation platforms, causal inference, or statistical methods for product and model evaluation
- Experience working with cloud-scale monitoring platforms such as Azure Monitor / Application Insights or equivalent
Compensation
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
Applied Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.
See all 253+ Applied Scientist jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Applied Scientist roles.
Get Access To All JobsTips for Finding TN Visa Sponsorship as an Applied Scientist
Align your degree to the scientific category
TN approval hinges on your specific degree field matching the Applied Scientist role. A computer science or statistics degree supports ML-focused positions; a biology or chemistry degree does not. Confirm the match before applying to avoid a port-of-entry denial.
Target employers with recent visa filing experience
Search for companies with recent visa filings for scientific roles. Employers already experienced with work visa sponsorship generally move faster and are less likely to confuse TN visa requirements with other sponsorship programs. Since TN visas don't involve government filings like other work visas, working with an employer familiar with sponsoring foreign workers means they understand the streamlined TN process and can prepare your support letter quickly.
Request a TN support letter before your start date
Your employer must produce a detailed support letter describing the scientific duties, your qualifying degree, and the TN category. Canadian citizens present this at the border; Mexican citizens need it for their consular appointment. Get a draft at least two weeks out.
Clarify TN status in your offer negotiation
Once you have an offer, confirm in writing that your employer will prepare the support letter. For Canadians, TN status is obtained directly at the U.S. border or port of entry—no advance government filings required. This streamlined process means many recruiters underestimate how straightforward the TN application actually is.
Use Migrate Mate to find TN-ready employers
Applied Scientist roles span tech, biotech, and research sectors, but not every employer understands TN eligibility. Use Migrate Mate to filter for companies actively sponsoring TN visa holders so you spend your time on employers already set up to hire you.
Prepare your credentials for scientific category scrutiny
Border officers and consular officials verify that your role involves applied scientific work, not general engineering or business analysis. Gather official transcripts, your degree certificate, and any published research or patents that demonstrate hands-on scientific application before your appointment.
Applied Scientist jobs are hiring across the US. Find yours.
Find Applied Scientist JobsApplied Scientist TN Visa: Frequently Asked Questions
Does an Applied Scientist role qualify for TN visa status?
Applied Scientist positions can qualify under the USMCA's Scientific Technician/Technologist category or adjacent scientific classifications, but the fit depends on your specific duties and degree. Roles centered on machine learning research, statistical modeling, or life sciences experimentation have a stronger case than general software development or product analytics work framed as applied science.
How does the TN visa compare to the H-1B for Applied Scientist positions?
TN visa sponsorship has no annual lottery and no cap for Canadian citizens, so you can start as soon as your employer is ready. H-1B selection is random and limited to 85,000 slots per fiscal year. The tradeoff is that TN requires you to maintain nonimmigrant intent and does not directly lead to a green card the way an H-1B petition can.
Where should I search for Applied Scientist jobs that offer TN visa sponsorship?
Generic job boards rarely filter by visa type, so you end up cold-applying to employers who may not know TN exists. Migrate Mate is built specifically for TN and other work visa job searches, letting you find companies that are already set up to sponsor Canadian and Mexican professionals in scientific roles.
Can a Mexican citizen get TN status for an Applied Scientist role?
Yes, Mexican citizens are eligible for TN status for qualifying scientific positions, but the process differs from Canada. You must schedule a consular interview at a U.S. embassy or consulate in Mexico, and TN visas for Mexican nationals are subject to a finite annual allocation under USMCA. Apply early in the fiscal year to avoid exhausting the cap.
What happens if my Applied Scientist TN visa is denied at the port of entry?
If a CBP officer denies your TN application at the border, you are typically permitted to withdraw the application and return to Canada without a formal refusal on your record. The most common reason is a mismatch between your stated duties and the USMCA scientific category. Work with your employer to revise the support letter and reapply with a clearer duty description.
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