TN Visa ML Engineer Jobs
ML Engineer roles qualify for TN visa sponsorship under USMCA's Computer Systems Analyst category when the position requires applying machine learning methods to analyze and solve systems problems. Canadian citizens can enter at the port of entry without a cap. Mexican citizens go through U.S. consular processing with a limited annual allocation.
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Get Access To All JobsABOUT THE ROLE
At Sigma, we're not just adding AI—we're building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we're pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast.
That's where you come in. As an AI/ML Engineer, you'll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma.
- Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities
- Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more
- Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features
- Tackle novel UX problems at the intersection of AI, BI, and apps
WHAT YOU BRING
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (required)
- 10+ years of experience building and deploying production-grade AI/ML systems
- Deep knowledge of machine learning, deep learning, and applied AI
- Experience across the full ML lifecycle: data curation, training, deployment, monitoring
- A track record of building things that ship—whether it's recommendations, search, machine translation, or something equally complex
- Experience adapting or training foundation models (language or multimodal) for novel domains
BONUS POINTS (OR SKILLS YOU'LL BUILD HERE)
- You've built agents that can plan, reason, and use tools
- You know your way around cloud infrastructure (AWS, GCP, Azure)
- You've worked in a fast-moving startup or high-growth environment
ADDITIONAL JOB DETAILS
The base salary range for this position is $240k - $270k annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.
About us:
Sigma is the AI apps and analytics platform connected to the cloud data warehouse. Using Sigma, business and technical teams can build intelligent, production-ready AI apps that accelerate and automate operational workflows. Sigma provides a spreadsheet interface, SQL and Python editors, visual builders, and native AI to help teams turn live data into interactive applications, analysis, reports, and embedded experiences.
Sigma announced its $200M in Series D financing in May 2024, to continue transforming BI through its innovations in AI infrastructure, data application development, enterprise-wide collaboration, and business user adoption. Spark Capital and Avenir Growth Capital co-led the Series D funding round, with additional participation from a group of past investors including Snowflake Ventures and Sutter Hill Ventures. The Series D funding, raised at a valuation 60% higher than the company's Series C round three years ago, promises to further accelerate Sigma's growth.
Come join us!
BENEFITS FOR OUR FULL-TIME EMPLOYEES:
- Equity
- Generous health benefits
- Flexible time off policy. Take the time off you need!
- Paid bonding time for all new parents
- Traditional and Roth 401k
- Commuter and FSA benefits
- Lunch Program
- Dog friendly office
Sigma Computing is an equal opportunity employer. We are committed to building a smart and strong team regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We look forward to learning how your experience can enable all of us to grow.
Note: We have an in-office work environment in all our offices in SF, NYC, and London.
OUR PRIVACY PRACTICES
When you submit a job application on this site, Sigma processes your personal data for the purposes of evaluating your candidacy for employment at Sigma and as otherwise needed throughout the recruitment and hiring process. Please review Sigma's Candidate Privacy Notice for more details. Please note that your personal data may be transferred to a country other than the one in which it was provided (including to USA, the UK, and Canada).
SIGMA'S USE OF AI
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
ABOUT THE ROLE
At Sigma, we're not just adding AI—we're building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we're pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast.
That's where you come in. As an AI/ML Engineer, you'll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma.
- Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities
- Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more
- Develop and scale AI/ML infrastructure that powers both internal tooling and customer-facing features
- Tackle novel UX problems at the intersection of AI, BI, and apps
WHAT YOU BRING
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (required)
- 10+ years of experience building and deploying production-grade AI/ML systems
- Deep knowledge of machine learning, deep learning, and applied AI
- Experience across the full ML lifecycle: data curation, training, deployment, monitoring
- A track record of building things that ship—whether it's recommendations, search, machine translation, or something equally complex
- Experience adapting or training foundation models (language or multimodal) for novel domains
BONUS POINTS (OR SKILLS YOU'LL BUILD HERE)
- You've built agents that can plan, reason, and use tools
- You know your way around cloud infrastructure (AWS, GCP, Azure)
- You've worked in a fast-moving startup or high-growth environment
ADDITIONAL JOB DETAILS
The base salary range for this position is $240k - $270k annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.
About us:
Sigma is the AI apps and analytics platform connected to the cloud data warehouse. Using Sigma, business and technical teams can build intelligent, production-ready AI apps that accelerate and automate operational workflows. Sigma provides a spreadsheet interface, SQL and Python editors, visual builders, and native AI to help teams turn live data into interactive applications, analysis, reports, and embedded experiences.
Sigma announced its $200M in Series D financing in May 2024, to continue transforming BI through its innovations in AI infrastructure, data application development, enterprise-wide collaboration, and business user adoption. Spark Capital and Avenir Growth Capital co-led the Series D funding round, with additional participation from a group of past investors including Snowflake Ventures and Sutter Hill Ventures. The Series D funding, raised at a valuation 60% higher than the company's Series C round three years ago, promises to further accelerate Sigma's growth.
Come join us!
BENEFITS FOR OUR FULL-TIME EMPLOYEES:
- Equity
- Generous health benefits
- Flexible time off policy. Take the time off you need!
- Paid bonding time for all new parents
- Traditional and Roth 401k
- Commuter and FSA benefits
- Lunch Program
- Dog friendly office
Sigma Computing is an equal opportunity employer. We are committed to building a smart and strong team regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We look forward to learning how your experience can enable all of us to grow.
Note: We have an in-office work environment in all our offices in SF, NYC, and London.
OUR PRIVACY PRACTICES
When you submit a job application on this site, Sigma processes your personal data for the purposes of evaluating your candidacy for employment at Sigma and as otherwise needed throughout the recruitment and hiring process. Please review Sigma's Candidate Privacy Notice for more details. Please note that your personal data may be transferred to a country other than the one in which it was provided (including to USA, the UK, and Canada).
SIGMA'S USE OF AI
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
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Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Engineer roles.
Get Access To All JobsTips for Finding TN Visa Sponsorship as a ML Engineer
Align your credentials to Computer Systems Analyst
TN approval for ML Engineer roles hinges on classification under Computer Systems Analyst. Your degree in computer science, mathematics, or a related field must map directly to that category. A mismatch in classification is the most common denial trigger for ML candidates.
Target employers with documented ML infrastructure
Seek out companies running production ML systems, not just data science experiments. Employers who already deploy model pipelines are more likely to frame your role in systems terms, which strengthens the specialty occupation argument CBP or a consular officer will scrutinize.
Request a detailed support letter from your employer
Your employer's support letter must describe your specific duties in systems analysis terms, not just 'train models' or 'build algorithms.' Push for language that connects ML engineering tasks to systems design, deployment architecture, and technical problem-solving for the organization.
Prepare for Canadians entering at the port of entry
Canadian citizens apply directly at a land border or airport port of entry without scheduling a consular appointment. Bring your job offer letter, credential documents, and employer support letter. CBP officers adjudicate on the spot, so a disorganized packet can cause delays or denial.
Search for sponsoring employers through Migrate Mate
Filtering job openings by TN visa compatibility saves time you'd otherwise spend cold-contacting employers who won't sponsor. Migrate Mate surfaces ML Engineer roles from employers already open to TN candidates, so you spend less effort on outreach that goes nowhere.
Verify the role qualifies before accepting an offer
Not every ML Engineer job title maps cleanly to a TN-eligible occupation. Before signing, confirm with the employer that the position's core duties center on computer systems analysis. Roles focused primarily on research or data labeling carry a higher risk of CBP pushback at entry.
ML Engineer jobs are hiring across the US. Find yours.
Find ML Engineer JobsML Engineer TN Visa: Frequently Asked Questions
Does ML Engineer qualify as a TN visa occupation?
ML Engineer isn't a listed TN occupation by title, but the role typically qualifies under the Computer Systems Analyst category. The job duties must center on analyzing, designing, and implementing computer systems solutions using machine learning methods. If the role is primarily research-oriented or lacks a clear systems component, a CBP officer may decline to classify it as TN-eligible.
How does TN compare to H-1B for ML Engineer roles?
TN has no annual lottery and no cap for Canadian citizens, so you can start working as soon as your application is approved, often the same day at the port of entry. H-1B requires winning a lottery with roughly a 25% selection rate and waiting until October 1 to begin work. For Mexican citizens, TN has a limited annual allocation, but consular processing is still faster than H-1B timelines.
Where can I find ML Engineer jobs that offer TN visa sponsorship?
Migrate Mate is built specifically for Canadian and Mexican professionals seeking TN-eligible roles. You can search ML Engineer positions filtered by TN visa compatibility, which removes the guesswork of figuring out which employers will support a TN filing. Most general job boards don't filter by visa type, so you end up spending time on applications that go nowhere for immigration reasons.
Can a Canadian ML Engineer apply for TN at the border without an attorney?
Yes. Canadian citizens don't need to file a petition with USCIS in advance. You present your application package directly to a CBP officer at a port of entry. That package must include a formal job offer letter, your employer's support letter describing the systems analyst duties, and evidence of your qualifying degree. Incomplete or poorly framed documentation is the main reason for same-day denials.
What happens to my TN status if my ML Engineer role shifts toward pure research?
TN status under Computer Systems Analyst is tied to the duties your employer described when you entered. If your role evolves significantly, such as moving from systems deployment to academic-style research, you may no longer meet the classification criteria. Your employer should issue an amended support letter and you should discuss whether a new TN entry or an alternative visa category is appropriate before your next renewal or travel.
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