Tech Lead Jobs in USA with Visa Sponsorship
Tech Lead roles are among the most consistently sponsored positions in U.S. tech. Most qualify as H-1B specialty occupations, and companies ranging from early-stage startups to Fortune 500s routinely file petitions for this title. Expect strong demand, competitive lottery odds, and a clear path to employer sponsorship. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsCompany Description
LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works.
Job Description
This role is based in either our Sunnyvale, San Francisco, New York, or Chicago offices. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. As part of the Product Operations organization, you will leverage one of the richest proprietary datasets in the world to lead high-impact initiatives that deepen intelligence across our members and customers and elevate product quality. We are seeking a talented and driven technical leader who excels at delivering world-class AI-powered analytic solutions, actionable insights, and measurable business impact. You will design and implement data-driven initiatives that create both immediate value and long-term strategic advantage. You bring strong technical acumen, product judgment, and business savvy, with applied expertise in modern AI tools and techniques. You combine analytical rigor with a growth mindset to generate scalable, data-driven learnings. You are comfortable navigating large, complex, and ambiguous data ecosystems and influencing cross-functional stakeholders through strong relationship-building and collaboration. This is a hands-on “player-coach” leadership role. You will architect solutions, write production-grade code using AI tools, and mentor a team of 3–4 data scientists and analytics engineers. You will own the end-to-end technical lifecycle of complex initiatives — from prototyping AI-driven concepts to deploying scalable, automated systems. Combining the analytical depth of a principal data scientist with executive-level storytelling, your primary goal is to architect and build agentic workflows, predictive models, and automated systems that fundamentally transform how operations teams operate.
Responsibilities
Architect & Build:
- Lead the hands-on design, development, and deployment of scalable data products, AI/ML models (e.g., member friction, customer impact, anomaly detection), and GenAI-powered agentic workflows.
Technical Strategy:
- Define the technical roadmap and architecture for the Product Operations Applied AI pillar, including key decisions on frameworks, tooling, and practices.
End-to-End Automation:
- Write high-quality, production-ready Python and SQL to build and maintain automated data pipelines, advanced analytics, and insight-delivery systems.
Applied AI Integration:
- Serve as the subject matter expert on applying modern AI, LLMs, and ML techniques (e.g., RAG, fine-tuning) to solve GTM business problems in partnership with Data Science and Engineering teams.
Technical Mentorship:
- Mentor and develop a team of data analysts and engineers, setting a high bar for technical rigor, code quality, and engineering best practices through a lead-by-example approach.
Executive Storytelling:
- Translate complex technical concepts and model outputs into clear, concise, and actionable narratives for senior GTM and Operations leadership.
Cross-Functional Partnership:
- Collaborate with Product, Engineering, and Data Science teams to operationalize and scale models from prototype to production, ensuring reliability and measurable business impact.
Qualifications
Basic Qualifications
- 7+ years of experience in data science, machine learning, or analytics engineering.
- 7+ years of experience in Python for data manipulation (pandas, NumPy), analytics, and ML (e.g., scikit-learn, TensorFlow, PyTorch).
- SQL experience with large-scale data warehouses (e.g., Presto, Trino, Spark SQL).
- 3+ years of experience with GenAI technologies and frameworks (e.g., LangChain, LLM APIs).
- 3+ years of architecting, building, and deploying machine learning models and/or automated data solutions in production environments.
- BA/BS in Computer Science, Statistics, Operations Research, Engineering, or a related quantitative field (or equivalent practical experience).
Preferred Qualifications
- MS or PhD in Computer Science, Statistics, or a related quantitative field.
- Experience with modern data stack and automation tools (e.g., Airflow, Databricks).
- Proven ability to lead ambiguous, complex technical initiatives from 0→1.
- Demonstrated experience influencing technical roadmaps in fast-moving environments.
- Resilient, resourceful, and self-directed with a strong bias for action.
- Passion for AI with a clear, strategic perspective on applying machine learning to drive business decisions.
Suggested Skills
- Python
- SQL
- Data Science
- Machine Learning
- Model Development & Deployment
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $150,000 to $243,000. Actual compensation is based on multiple factors including skills, experience, certifications, and location. Compensation may vary in other locations due to cost-of-labor considerations. Total compensation may include annual performance bonus, stock, benefits, and other applicable incentive compensation plans.
Additional Information
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
- Documents in alternate formats or read aloud to you
- Having interviews in an accessible location
- Being accompanied by a service dog
- Having a sign language interpreter present for the interview
A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
Company Description
LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works.
Job Description
This role is based in either our Sunnyvale, San Francisco, New York, or Chicago offices. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. As part of the Product Operations organization, you will leverage one of the richest proprietary datasets in the world to lead high-impact initiatives that deepen intelligence across our members and customers and elevate product quality. We are seeking a talented and driven technical leader who excels at delivering world-class AI-powered analytic solutions, actionable insights, and measurable business impact. You will design and implement data-driven initiatives that create both immediate value and long-term strategic advantage. You bring strong technical acumen, product judgment, and business savvy, with applied expertise in modern AI tools and techniques. You combine analytical rigor with a growth mindset to generate scalable, data-driven learnings. You are comfortable navigating large, complex, and ambiguous data ecosystems and influencing cross-functional stakeholders through strong relationship-building and collaboration. This is a hands-on “player-coach” leadership role. You will architect solutions, write production-grade code using AI tools, and mentor a team of 3–4 data scientists and analytics engineers. You will own the end-to-end technical lifecycle of complex initiatives — from prototyping AI-driven concepts to deploying scalable, automated systems. Combining the analytical depth of a principal data scientist with executive-level storytelling, your primary goal is to architect and build agentic workflows, predictive models, and automated systems that fundamentally transform how operations teams operate.
Responsibilities
Architect & Build:
- Lead the hands-on design, development, and deployment of scalable data products, AI/ML models (e.g., member friction, customer impact, anomaly detection), and GenAI-powered agentic workflows.
Technical Strategy:
- Define the technical roadmap and architecture for the Product Operations Applied AI pillar, including key decisions on frameworks, tooling, and practices.
End-to-End Automation:
- Write high-quality, production-ready Python and SQL to build and maintain automated data pipelines, advanced analytics, and insight-delivery systems.
Applied AI Integration:
- Serve as the subject matter expert on applying modern AI, LLMs, and ML techniques (e.g., RAG, fine-tuning) to solve GTM business problems in partnership with Data Science and Engineering teams.
Technical Mentorship:
- Mentor and develop a team of data analysts and engineers, setting a high bar for technical rigor, code quality, and engineering best practices through a lead-by-example approach.
Executive Storytelling:
- Translate complex technical concepts and model outputs into clear, concise, and actionable narratives for senior GTM and Operations leadership.
Cross-Functional Partnership:
- Collaborate with Product, Engineering, and Data Science teams to operationalize and scale models from prototype to production, ensuring reliability and measurable business impact.
Qualifications
Basic Qualifications
- 7+ years of experience in data science, machine learning, or analytics engineering.
- 7+ years of experience in Python for data manipulation (pandas, NumPy), analytics, and ML (e.g., scikit-learn, TensorFlow, PyTorch).
- SQL experience with large-scale data warehouses (e.g., Presto, Trino, Spark SQL).
- 3+ years of experience with GenAI technologies and frameworks (e.g., LangChain, LLM APIs).
- 3+ years of architecting, building, and deploying machine learning models and/or automated data solutions in production environments.
- BA/BS in Computer Science, Statistics, Operations Research, Engineering, or a related quantitative field (or equivalent practical experience).
Preferred Qualifications
- MS or PhD in Computer Science, Statistics, or a related quantitative field.
- Experience with modern data stack and automation tools (e.g., Airflow, Databricks).
- Proven ability to lead ambiguous, complex technical initiatives from 0→1.
- Demonstrated experience influencing technical roadmaps in fast-moving environments.
- Resilient, resourceful, and self-directed with a strong bias for action.
- Passion for AI with a clear, strategic perspective on applying machine learning to drive business decisions.
Suggested Skills
- Python
- SQL
- Data Science
- Machine Learning
- Model Development & Deployment
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $150,000 to $243,000. Actual compensation is based on multiple factors including skills, experience, certifications, and location. Compensation may vary in other locations due to cost-of-labor considerations. Total compensation may include annual performance bonus, stock, benefits, and other applicable incentive compensation plans.
Additional Information
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation. Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
- Documents in alternate formats or read aloud to you
- Having interviews in an accessible location
- Being accompanied by a service dog
- Having a sign language interpreter present for the interview
A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
How to Get Visa Sponsorship in Tech Lead
Target companies with H-1B filing history
Employers who have sponsored Tech Leads before are far more likely to do it again. Prioritize companies with established immigration programs over startups filing their first-ever petition, where internal processes are untested and timelines unpredictable.
Get the job title right on your LCA
"Tech Lead" can cover a wide range of responsibilities. Make sure your employer's Labor Condition Application reflects a title and job duties that clearly map to a specialty occupation requiring a bachelor's degree in a specific technical field, not generic management.
Document your degree-to-role alignment
USCIS scrutinizes Tech Lead petitions where the degree field feels broad. A computer science or software engineering degree strengthens your case significantly. If your degree is in a related field, gather evidence linking your coursework directly to the technical duties you'll perform.
Negotiate cap-exempt employer options
Universities, nonprofit research institutions, and government research organizations are exempt from the H-1B lottery. A Tech Lead role at one of these employers means your petition can be filed any time of year, bypassing the annual cap entirely.
Prepare for a Request for Evidence
Tech Lead petitions receive RFEs at above-average rates because the title blends technical and managerial work. Proactively include an org chart, detailed duty breakdown, and documentation showing the role requires at least a bachelor's degree in a specific technical discipline.
Use Migrate Mate to filter for sponsoring employers
Not every job posting that says "open to sponsorship" will follow through. Migrate Mate surfaces Tech Lead roles from employers with verified sponsorship track records, so you're applying to companies that have actually filed petitions before, not just ones that say they will.
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Get Access To All JobsFrequently Asked Questions
Does a Tech Lead role qualify as an H-1B specialty occupation?
Yes, in most cases. Tech Leads typically require a bachelor's degree or higher in computer science, software engineering, or a related technical field, which satisfies the specialty occupation standard. The risk comes when the role is framed as primarily managerial. USCIS looks for job duties that genuinely require theoretical and practical application of a specific technical discipline, so the petition needs to reflect that clearly.
What degree do I need to qualify for H-1B sponsorship as a Tech Lead?
A bachelor's degree in computer science, software engineering, information technology, or a closely related field is the standard. Your degree field needs to align with the specific technical duties in the role, not just the industry. If your degree is in a different but related field, a credential evaluation and supporting documentation can help establish equivalency. A general business or management degree alone is unlikely to be sufficient.
Are Tech Lead H-1B petitions more likely to get an RFE than other engineering roles?
Yes. Because Tech Lead is a hybrid title that combines hands-on engineering with team leadership, USCIS sometimes questions whether the role is truly a specialty occupation or primarily supervisory. Petitions without a detailed technical duty breakdown are especially vulnerable. Including an organizational chart, a percentage breakdown of technical versus managerial duties, and documentation of required technical skills significantly reduces RFE risk.
Can I get sponsored as a Tech Lead at a startup?
Yes, but it takes more diligence. Early-stage startups often lack in-house immigration counsel, which increases the risk of procedural errors or delays. The company also needs to demonstrate ability to pay the prevailing wage. Startups that have previously filed H-1B petitions are lower risk. Migrate Mate lists Tech Lead openings filtered by employers with documented sponsorship history, which helps identify startups that have successfully navigated the process before.
Does work experience substitute for a degree when applying for a Tech Lead H-1B?
It can, but the bar is high. USCIS accepts three years of specialized work experience as equivalent to one year of formal education. To qualify without a four-year degree, you'd typically need 12 years of progressively responsible experience directly relevant to the Tech Lead duties. The experience must be documented through employer letters and must map specifically to the technical field the role requires, not just general engineering work.
What is the prevailing wage requirement for sponsored Tech Lead jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.
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