Lead Machine Learning Engineer Visa Sponsorship Jobs in North Carolina
Lead machine learning engineer visa sponsorship jobs in North Carolina are concentrated in the Research Triangle, where employers like Red Hat, Lenovo, and Pendo anchor a growing AI sector. SAS Institute in Cary and biotech firms in Durham and Raleigh also hire at this level, drawing on deep university pipelines from NC State, Duke, and UNC Chapel Hill.
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Get Access To All JobsINTRODUCTION
DT (NASDAQ: APPS) is unifying the full mobile experience. Our growth platform powers the mobile ecosystem by bringing together advertisers, app developers, and device partners, to create a unique and premium value exchange, that results in a personalized and seamless mobile device experience.
At DT, we move fast, think big, and build collaboratively. We believe great ideas can come from anywhere, and we trust our teams to take ownership, challenge convention, and make an impact from day one.
Here, you’ll have the opportunity to grow your career while contributing to products and experiences used by millions around the world.
With us, you will enjoy competitive compensation, equity awards, and a comprehensive benefits package designed to invest in your total well-being, all within a hybrid and flexible work environment.
ROLE AND RESPONSIBILITIES
As a Lead Data Scientist, you will serve as a technical authority and strategic partner across engineering, product, and executive leadership. You will define technical roadmaps, architect high-impact ML and experimentation frameworks, and set the standard for data science excellence across DT’s global marketplace — from bidding efficacy and audience curation to measurement, attribution, and enterprise experimentation.
About the Lead Data Scientist role:
- Strategic Problem Framing & Vision: Lead the translation of complex, business challenges into multi-quarter data science roadmaps that directly shape product strategy and commercial outcomes
- Experimentation Architecture: Drive the methodology, design, and standards for DT’s centralized experimentation framework — serving as the primary authority on causal inference, A/B testing, and hypothesis validation across product surfaces
- Advanced Modeling & System Architecture: Architect and oversee the development of production-grade statistical and ML models for bid optimization, audience segmentation, recommendations, and user lifetime value (LTV)
- Real-Time Data Intelligence: Direct the strategy for time-series forecasting and real-time event processing to enhance automated decisioning, yield optimization, and recommendation engines
- Engineering Partnership & Productionization: Partner with ML Infrastructure and Data Engineering leads to establish best practices for model deployment, monitoring, and integration
- Practical Application: Proven ability to take theoretical state of the art advances and apply them to DT’s engines in a strategic and scalable manner
- Technical Leadership & Mentorship: Elevate the technical rigor of the data science organization. Mentor senior and mid-level scientists, establish code and methodology standards, and foster an evidence-based culture across the company
- Executive Influence: Translate deep technical findings into strategic narratives for executive stakeholders, influencing product strategy and commercial investments
BASIC QUALIFICATIONS
- Experience: 8+ years of progressive experience in data science, quantitative analysis, or machine learning, with a track record of technical leadership in AdTech, two-sided marketplaces, or consumer-scale data platforms
- Technical Mastery: Expertise in advanced statistical modeling, causal inference, experimental design, and machine learning architectures (regression, classification, time-series, clustering, deep learning, multi-armed bandits, and large language models)
- Stack & Scale: Expert fluency in Python (or R), SQL, and handling petabyte-scale data within cloud infrastructure (e.g., Databricks, Spark, Snowflake, AWS/GCP)
- Systemic Thinking: Proven ability to look beyond individual analyses to design scalable tools, reusable metrics frameworks, and automated modeling pipelines
- Cross-Functional Leadership: Exceptional communication and alignment skills, with a history of driving technical strategy across matrixed product, engineering, and business organizations
PREFERRED QUALIFICATIONS
- Hands-on experience architecting metrics semantic layers or enterprise experimentation tools
- Deep domain expertise in real-time bidding (RTB) auctions, algorithmic yield management, large scale content recommendation engines, or advanced attribution methodologies
- Masters or Ph.D. in a quantitative field (Statistics, Computer Science, Economics, Operations Research, or Physics)
DT (NASDAQ: APPS) is a mobile growth platform that powers superior experiences and outcomes for advertisers, app developers, carriers, OEMs, and publishers worldwide.
Our technology connects brands and apps with consumers across devices, apps, and mobile environments — helping partners drive awareness, acquisition, engagement, and monetization through intelligent, integrated experiences.
LOCATION
Headquartered in Austin, Texas, DT operates globally across North America, EMEA, APAC, and LATAM.
DT is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We welcome people of different backgrounds, experiences, abilities, and perspectives, and believe teams with different points of view build better products, ideas, and experiences.
INTRODUCTION
DT (NASDAQ: APPS) is unifying the full mobile experience. Our growth platform powers the mobile ecosystem by bringing together advertisers, app developers, and device partners, to create a unique and premium value exchange, that results in a personalized and seamless mobile device experience.
At DT, we move fast, think big, and build collaboratively. We believe great ideas can come from anywhere, and we trust our teams to take ownership, challenge convention, and make an impact from day one.
Here, you’ll have the opportunity to grow your career while contributing to products and experiences used by millions around the world.
With us, you will enjoy competitive compensation, equity awards, and a comprehensive benefits package designed to invest in your total well-being, all within a hybrid and flexible work environment.
ROLE AND RESPONSIBILITIES
As a Lead Data Scientist, you will serve as a technical authority and strategic partner across engineering, product, and executive leadership. You will define technical roadmaps, architect high-impact ML and experimentation frameworks, and set the standard for data science excellence across DT’s global marketplace — from bidding efficacy and audience curation to measurement, attribution, and enterprise experimentation.
About the Lead Data Scientist role:
- Strategic Problem Framing & Vision: Lead the translation of complex, business challenges into multi-quarter data science roadmaps that directly shape product strategy and commercial outcomes
- Experimentation Architecture: Drive the methodology, design, and standards for DT’s centralized experimentation framework — serving as the primary authority on causal inference, A/B testing, and hypothesis validation across product surfaces
- Advanced Modeling & System Architecture: Architect and oversee the development of production-grade statistical and ML models for bid optimization, audience segmentation, recommendations, and user lifetime value (LTV)
- Real-Time Data Intelligence: Direct the strategy for time-series forecasting and real-time event processing to enhance automated decisioning, yield optimization, and recommendation engines
- Engineering Partnership & Productionization: Partner with ML Infrastructure and Data Engineering leads to establish best practices for model deployment, monitoring, and integration
- Practical Application: Proven ability to take theoretical state of the art advances and apply them to DT’s engines in a strategic and scalable manner
- Technical Leadership & Mentorship: Elevate the technical rigor of the data science organization. Mentor senior and mid-level scientists, establish code and methodology standards, and foster an evidence-based culture across the company
- Executive Influence: Translate deep technical findings into strategic narratives for executive stakeholders, influencing product strategy and commercial investments
BASIC QUALIFICATIONS
- Experience: 8+ years of progressive experience in data science, quantitative analysis, or machine learning, with a track record of technical leadership in AdTech, two-sided marketplaces, or consumer-scale data platforms
- Technical Mastery: Expertise in advanced statistical modeling, causal inference, experimental design, and machine learning architectures (regression, classification, time-series, clustering, deep learning, multi-armed bandits, and large language models)
- Stack & Scale: Expert fluency in Python (or R), SQL, and handling petabyte-scale data within cloud infrastructure (e.g., Databricks, Spark, Snowflake, AWS/GCP)
- Systemic Thinking: Proven ability to look beyond individual analyses to design scalable tools, reusable metrics frameworks, and automated modeling pipelines
- Cross-Functional Leadership: Exceptional communication and alignment skills, with a history of driving technical strategy across matrixed product, engineering, and business organizations
PREFERRED QUALIFICATIONS
- Hands-on experience architecting metrics semantic layers or enterprise experimentation tools
- Deep domain expertise in real-time bidding (RTB) auctions, algorithmic yield management, large scale content recommendation engines, or advanced attribution methodologies
- Masters or Ph.D. in a quantitative field (Statistics, Computer Science, Economics, Operations Research, or Physics)
DT (NASDAQ: APPS) is a mobile growth platform that powers superior experiences and outcomes for advertisers, app developers, carriers, OEMs, and publishers worldwide.
Our technology connects brands and apps with consumers across devices, apps, and mobile environments — helping partners drive awareness, acquisition, engagement, and monetization through intelligent, integrated experiences.
LOCATION
Headquartered in Austin, Texas, DT operates globally across North America, EMEA, APAC, and LATAM.
DT is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We welcome people of different backgrounds, experiences, abilities, and perspectives, and believe teams with different points of view build better products, ideas, and experiences.
Lead Machine Learning Engineer Job Roles in North Carolina
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Search Lead Machine Learning Engineer Jobs in North CarolinaLead Machine Learning Engineer Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for lead machine learning engineers in North Carolina?
Major sponsors in North Carolina include SAS Institute in Cary, Red Hat and IBM in Raleigh, and Lenovo's North America headquarters in Morrisville. Biotech and life sciences companies in the Research Triangle Park area, such as Biogen and Syneos Health, also sponsor senior ML engineering roles. Financial services firms with regional operations in Charlotte, including Bank of America and Truist, file H-1B visa petitions for lead-level machine learning positions.
What visa types realistically apply to lead machine learning engineer roles in North Carolina?
The H-1B is the most common path, since lead machine learning engineer roles qualify as specialty occupations requiring a directly related bachelor's degree or higher. Canadian and Mexican nationals may qualify under TN visa status as engineers under USMCA. Australian nationals can pursue the E-3 visa, which requires a specialty occupation and a job offer but has no lottery. Singapore nationals may use the H-1B1 and Chilean nationals the H-1B1 Chile variant. Qualified candidates with a STEM-designated degree already on OPT may also work while transitioning sponsorship.
Which cities in North Carolina have the most lead machine learning engineer sponsorship jobs?
Raleigh and Durham together form the core of North Carolina's ML hiring activity, anchored by Research Triangle Park's density of tech, biotech, and analytics employers. Cary is a secondary hub, primarily driven by SAS Institute's large engineering workforce. Charlotte has grown as a financial technology center, with banks and fintech companies sponsoring senior ML engineers. Smaller activity exists in Chapel Hill and Morrisville, particularly near Lenovo's U.S. operations.
How to find lead machine learning engineer visa sponsorship jobs in North Carolina?
Migrate Mate lists North Carolina employers with verified visa sponsorship history for lead machine learning engineer roles, so you can focus on companies already familiar with the H-1B, E-3, or TN process at the senior engineering level. The Research Triangle and Charlotte markets are both represented. Because these roles require demonstrated leadership and ML expertise, filtering by employers who have sponsored equivalent senior positions in prior years helps prioritize realistic opportunities over long-shot applications.
Are there state-specific factors that affect visa sponsorship for lead ML engineers in North Carolina?
North Carolina's Research Triangle Park is one of the most concentrated technology and life sciences corridors on the East Coast, which means employers here tend to have established immigration support infrastructure and in-house or retained immigration counsel. NC State's strong computer science and data science programs, combined with Duke and UNC Chapel Hill, create a steady local pipeline that employers draw from. This familiarity generally means that lead-level ML roles at established Research Triangle employers are more likely to come with sponsorship support than at smaller regional firms.
What is the prevailing wage for sponsored lead machine learning engineer jobs in North Carolina?
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.