AI ML Engineer Jobs at SentiLink with Visa Sponsorship
SentiLink builds fraud and identity risk products powered by machine learning, and AI ML Engineer roles here sit at the intersection of applied research and production systems. The company has an established path for sponsoring international talent, including support for F-1 OPT transitions and employment-based Green Card categories.
See All AI ML Engineer at SentiLink JobsOverview
Showing 5 of 29+ AI ML Engineer Jobs at SentiLink jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 29+ AI ML Engineer Jobs at SentiLink
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineer Jobs at SentiLink.
Get Access To All JobsINTRODUCTION
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States, replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate. We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50 list every year since 2023. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity. SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.
ROLE
We’re looking for a founding Senior Machine Learning Engineer to help scale and operationalize our ML systems end-to-end. This is a highly technical role focused on building the infrastructure, tooling, and processes that allow our Data Science team to develop, deploy, monitor, and iterate on machine learning models efficiently and safely. This person will be a foundational owner of our ML platform and will define the interfaces between Data Science, Engineering, and Infrastructure. You’ll work on systems that power real-time production ML, ensuring we can confidently ship models, measure their impact, and detect issues early. This is a high-ownership role for someone who wants to build ML systems that power real-world fraud prevention at scale.
Technologies:
Python, SQL, MLflow, Datadog, Grafana, Prometheus, Airflow/Dagster/Prefect, Docker, Kubernetes, AWS, PostgreSQL, Git, CI/CD pipelines, GitHub Actions.
Responsibilities
- Own SentiLink’s real-time ML model monitoring domain, leading the design, implementation, and ongoing improvement of monitoring systems and workflows.
- Own our ML experimentation, model tracking, and versioning infrastructure, ensuring strong reproducibility and visibility across the model lifecycle.
- Drive improvements to the model development process, reducing inefficiencies, improving code quality, resolving DS tooling gaps, and enabling faster iteration.
- Serve as the primary technical owner of key touchpoints and interfaces between Data Science and Engineering/Infrastructure, defining standards and workflows.
- Support efforts to optimize model behavior in production, including latency, reliability, maintainability, and operational best practices.
- Investigate and diagnose model performance issues on an ad-hoc basis, including partner escalations and analysis of model behavior in real-world scenarios.
- Evaluate, prototype, and recommend new ML infrastructure, tools, and data capabilities, partnering with DS to validate impact and support adoption.
REQUIREMENTS
- 5+ years of relevant experience, with a degree in Computer Science, Engineering, Mathematics, or a related technical field.
- Strong software engineering fundamentals, with proficiency in Python and SQL, and strong working knowledge of Git and modern CI/CD workflows.
- Hands-on experience with ML experimentation and model tracking tools.
- Strong proficiency with model monitoring and observability tooling.
- Experience with ML infrastructure and orchestration technologies, such as Docker, Kubernetes, and workflow orchestration frameworks.
- Familiarity with model serving and deployment frameworks.
- Proven experience deploying and operating machine learning models as production services, with an emphasis on reliability and performance.
- Demonstrated ability to build 0-to-1 prototypes and proof-of-concepts, rapidly standing up ML services and experimentation environments.
- Experience designing, building, and optimizing ML pipelines for training, evaluation, and deployment.
- Highly adaptable and able to learn quickly in fast-moving environments with evolving technical requirements.
- Candidates must be legally authorized to work in the United States and must live in the United States.
COMPENSATION
$170,000/year - $240,000/year + equity + benefits [across Senior & Staff level]
PERKS
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend, and more!
CORPORATE VALUES
- Follow Through
- Deep Understanding
- Whatever It Takes
- Do Something Smart
INTRODUCTION
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States, replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate. We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50 list every year since 2023. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity. SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.
ROLE
We’re looking for a founding Senior Machine Learning Engineer to help scale and operationalize our ML systems end-to-end. This is a highly technical role focused on building the infrastructure, tooling, and processes that allow our Data Science team to develop, deploy, monitor, and iterate on machine learning models efficiently and safely. This person will be a foundational owner of our ML platform and will define the interfaces between Data Science, Engineering, and Infrastructure. You’ll work on systems that power real-time production ML, ensuring we can confidently ship models, measure their impact, and detect issues early. This is a high-ownership role for someone who wants to build ML systems that power real-world fraud prevention at scale.
Technologies:
Python, SQL, MLflow, Datadog, Grafana, Prometheus, Airflow/Dagster/Prefect, Docker, Kubernetes, AWS, PostgreSQL, Git, CI/CD pipelines, GitHub Actions.
Responsibilities
- Own SentiLink’s real-time ML model monitoring domain, leading the design, implementation, and ongoing improvement of monitoring systems and workflows.
- Own our ML experimentation, model tracking, and versioning infrastructure, ensuring strong reproducibility and visibility across the model lifecycle.
- Drive improvements to the model development process, reducing inefficiencies, improving code quality, resolving DS tooling gaps, and enabling faster iteration.
- Serve as the primary technical owner of key touchpoints and interfaces between Data Science and Engineering/Infrastructure, defining standards and workflows.
- Support efforts to optimize model behavior in production, including latency, reliability, maintainability, and operational best practices.
- Investigate and diagnose model performance issues on an ad-hoc basis, including partner escalations and analysis of model behavior in real-world scenarios.
- Evaluate, prototype, and recommend new ML infrastructure, tools, and data capabilities, partnering with DS to validate impact and support adoption.
REQUIREMENTS
- 5+ years of relevant experience, with a degree in Computer Science, Engineering, Mathematics, or a related technical field.
- Strong software engineering fundamentals, with proficiency in Python and SQL, and strong working knowledge of Git and modern CI/CD workflows.
- Hands-on experience with ML experimentation and model tracking tools.
- Strong proficiency with model monitoring and observability tooling.
- Experience with ML infrastructure and orchestration technologies, such as Docker, Kubernetes, and workflow orchestration frameworks.
- Familiarity with model serving and deployment frameworks.
- Proven experience deploying and operating machine learning models as production services, with an emphasis on reliability and performance.
- Demonstrated ability to build 0-to-1 prototypes and proof-of-concepts, rapidly standing up ML services and experimentation environments.
- Experience designing, building, and optimizing ML pipelines for training, evaluation, and deployment.
- Highly adaptable and able to learn quickly in fast-moving environments with evolving technical requirements.
- Candidates must be legally authorized to work in the United States and must live in the United States.
COMPENSATION
$170,000/year - $240,000/year + equity + benefits [across Senior & Staff level]
PERKS
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend, and more!
CORPORATE VALUES
- Follow Through
- Deep Understanding
- Whatever It Takes
- Do Something Smart
See all 29+ AI ML Engineer at SentiLink jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineer at SentiLink roles.
Get Access To All JobsTips for Finding AI ML Engineer Jobs at SentiLink Jobs
Align your ML portfolio to fraud detection
SentiLink's core product is identity fraud prevention. Before applying, reframe your portfolio projects around anomaly detection, classification on imbalanced datasets, or graph-based identity modeling. Reviewers will connect your background to their domain faster.
Confirm OPT STEM extension eligibility early
AI ML Engineer roles at SentiLink fall under STEM-designated SOC codes, making you eligible for a 24-month OPT extension. Verify your degree program's CIP code qualifies with your Designated School Official before your initial OPT period starts running.
Target roles with production ML scope
SentiLink posts both research-leaning and production-focused ML roles. Positions with ownership over deployed models and latency-sensitive inference pipelines are more likely to meet the specialty occupation threshold USCIS applies when evaluating H-1B petitions.
Use Migrate Mate to surface SentiLink openings
SentiLink's sponsored AI ML Engineer positions don't always appear on general job boards with sponsorship flags intact. Use Migrate Mate to filter specifically for SentiLink roles that include visa sponsorship, so you're applying to verified openings.
Prepare for a technical screen on applied ML systems
SentiLink's interview process tests both modeling fundamentals and systems design for scale. Prepare to discuss feature engineering pipelines, model monitoring in production, and how you'd handle concept drift in a fraud detection context where ground truth labels are delayed.
AI ML Engineer at SentiLink jobs are hiring across the US. Find yours.
Find AI ML Engineer at SentiLink JobsFrequently Asked Questions
Does SentiLink sponsor H-1B visas for AI ML Engineers?
SentiLink has a history of supporting work visa sponsorship for technical roles, and AI ML Engineer positions fall within the specialty occupation framework that H-1B petitions require. Because the H-1B is subject to an annual cap and lottery, your timing matters. If you're already in a cap-exempt status or hold an H-1B with another employer, a transfer may be faster than waiting for the next lottery cycle.
How do I apply for AI ML Engineer jobs at SentiLink?
You can find AI ML Engineer openings at SentiLink through their careers page or through Migrate Mate, which surfaces roles filtered by visa sponsorship eligibility. Tailor your application to highlight production ML experience, particularly in domains involving structured tabular data, fraud signals, or risk modeling. SentiLink's process typically includes a recruiter screen, a technical assessment, and multiple engineering interviews.
Which visa types does SentiLink commonly use for AI ML Engineer roles?
SentiLink sponsors F-1 OPT for recent graduates, including the 24-month STEM OPT extension available to qualifying ML and computer science degree holders. For longer-term work authorization, the company supports employment-based Green Card categories including EB-2 and EB-3, which require a PERM labor certification filed with the DOL. TN status is also an option for Canadian and Mexican nationals whose role qualifies under USMCA occupation categories.
What qualifications does SentiLink expect for AI ML Engineer roles?
SentiLink's AI ML Engineer roles typically require a bachelor's or master's degree in computer science, statistics, or a closely related quantitative field. Practical experience building and deploying supervised learning models is expected, not just academic project work. Familiarity with Python-based ML frameworks, feature engineering at scale, and working with imbalanced or noisy datasets is directly relevant to their fraud and identity risk products.
How does the sponsorship timeline work for an AI ML Engineer at SentiLink?
If you're on F-1 OPT, you can begin working immediately while SentiLink files a STEM OPT extension before your initial period expires. H-1B sponsorship follows USCIS's October 1 start date, so your employer needs to file in March for a role starting in the fall. For Green Card sponsorship through PERM, the DOL labor certification process alone typically takes six months to over a year before the immigrant petition stage.
See which AI ML Engineer at SentiLink employers are hiring and sponsoring visas right now.
Search AI ML Engineer at SentiLink Jobs