Machine Learning Engineer Jobs at Tiger Analytics with Visa Sponsorship
Tiger Analytics hires Machine Learning Engineers to build production-grade models and analytics solutions for global enterprise clients. The company has a consistent track record of sponsoring work visas for this function, supporting candidates across multiple visa pathways from OPT through to long-term employment sponsorship.
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Get Access To All JobsINTRODUCTION
Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
ROLE AND RESPONSIBILITIES:
- Design, build, and optimize high-performance APIs and microservices using Python (Fast API) deployed on AWS Fargate (ECS)
- Integrate LLM and Generative AI APIs using providers such as AWS Bedrock, OpenAI, and others
- Collaborate with ML and DevOps teams to design CI/CD and MLOps pipelines within the AWS ecosystem
- Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems
- (Preferred) Leverage familiarity with Bedrock Agent Core services to integrate intelligent agent capabilities
- Develop and maintain JSON RESTful APIs, adhering to OpenAI API conventions and best practices
BASIC QUALIFICATIONS:
- 5+ years of hands-on software development experience with Python
- Proven expertise in FastAPI and microservice architecture
- Strong understanding of cloud-native applications, container orchestration (ECS, Docker), and AWS tools
- Proficiency in LLM API integration and working with Generative AI frameworks
- Experience implementing CI/CD, IaC, and ML pipelines across AWS environments
- Familiarity with Bedrock AgentCore or other agentic systems (nice to have)
PREFERRED QUALIFICATIONS:
You'll be part of an innovative team building the next generation of AI-driven applications, where scalability, performance, and intelligent automation converge. This is an opportunity to push boundaries in Agentic AI infrastructure development in a supportive, fast-moving environment.
BENEFITS
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
INTRODUCTION
Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
ROLE AND RESPONSIBILITIES:
- Design, build, and optimize high-performance APIs and microservices using Python (Fast API) deployed on AWS Fargate (ECS)
- Integrate LLM and Generative AI APIs using providers such as AWS Bedrock, OpenAI, and others
- Collaborate with ML and DevOps teams to design CI/CD and MLOps pipelines within the AWS ecosystem
- Contribute to architectural decisions around scalability, latency management, and backend efficiency for AI-powered systems
- (Preferred) Leverage familiarity with Bedrock Agent Core services to integrate intelligent agent capabilities
- Develop and maintain JSON RESTful APIs, adhering to OpenAI API conventions and best practices
BASIC QUALIFICATIONS:
- 5+ years of hands-on software development experience with Python
- Proven expertise in FastAPI and microservice architecture
- Strong understanding of cloud-native applications, container orchestration (ECS, Docker), and AWS tools
- Proficiency in LLM API integration and working with Generative AI frameworks
- Experience implementing CI/CD, IaC, and ML pipelines across AWS environments
- Familiarity with Bedrock AgentCore or other agentic systems (nice to have)
PREFERRED QUALIFICATIONS:
You'll be part of an innovative team building the next generation of AI-driven applications, where scalability, performance, and intelligent automation converge. This is an opportunity to push boundaries in Agentic AI infrastructure development in a supportive, fast-moving environment.
BENEFITS
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
See all 40+ Machine Learning Engineer at Tiger Analytics jobs
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Get Access To All JobsTips for Finding Machine Learning Engineer Jobs at Tiger Analytics Jobs
Align your portfolio to production ML work
Tiger Analytics deploys models at scale for enterprise clients, not research prototypes. Before applying, make sure your portfolio shows end-to-end ML pipelines, model deployment, and real business impact rather than academic or Kaggle-style projects.
Target client-facing ML delivery roles specifically
Tiger Analytics structures hiring around client delivery teams, not internal product squads. Machine Learning Engineer roles here typically involve consulting-style engagements, so frame your experience around cross-functional collaboration and delivering solutions to external stakeholders.
Use Migrate Mate to filter open ML roles by visa type
Searching broadly across job boards won't tell you which openings Tiger Analytics is actively sponsoring. Migrate Mate surfaces their sponsored Machine Learning Engineer positions so you can apply directly to roles where your visa type is supported.
Understand how TN status applies to ML roles
Canadian and Mexican nationals can pursue TN status for qualifying ML Engineering positions under the Computer Systems Analyst or Engineer category. Confirm with the hiring team that your specific role description maps to a TN-eligible occupation before accepting an offer.
Ask about PERM timing before signing an offer
H-1B holders targeting a Green Card path should ask directly whether Tiger Analytics initiates PERM labor certification and at what point in your tenure. DOL processing backlogs mean earlier filing significantly affects your long-term work authorization timeline.
Machine Learning Engineer at Tiger Analytics jobs are hiring across the US. Find yours.
Find Machine Learning Engineer at Tiger Analytics JobsFrequently Asked Questions
Does Tiger Analytics sponsor H-1B visas for Machine Learning Engineers?
Yes, Tiger Analytics sponsors H-1B visas for Machine Learning Engineers. The company has an established sponsorship process for this role and participates in the annual H-1B cap lottery. If you're already on H-1B status with another employer, Tiger Analytics can also file an H-1B transfer, which lets you start work once the petition is filed rather than waiting for approval.
How do I apply for Machine Learning Engineer jobs at Tiger Analytics?
You can apply directly through Tiger Analytics's careers page, or use Migrate Mate to browse their currently open Machine Learning Engineer positions filtered by visa sponsorship type. Before applying, tailor your resume to reflect production ML experience, model deployment, and client-facing delivery work, as Tiger Analytics hires for applied engineering roles rather than pure research positions.
Which visa types does Tiger Analytics commonly sponsor for Machine Learning Engineer roles?
Tiger Analytics supports multiple visa pathways for Machine Learning Engineers, including H-1B, F-1 OPT and CPT, TN, and employment-based Green Cards through EB-2 or EB-3 classifications. F-1 students in their OPT period can begin work authorization immediately provided Tiger Analytics's E-Verify enrollment is confirmed, which is required for STEM OPT extensions.
What qualifications and experience does Tiger Analytics expect from Machine Learning Engineer candidates?
Tiger Analytics typically looks for hands-on experience building and deploying ML models in production environments, strong proficiency in Python and common ML frameworks such as TensorFlow or PyTorch, and familiarity with cloud platforms like AWS, GCP, or Azure. Because the work is client-facing, the ability to communicate model outputs and trade-offs to non-technical stakeholders is valued alongside technical depth.
How do I time my application around the H-1B cap and OPT expiration?
H-1B cap petitions can only be filed once per year, with USCIS opening registration in March for an October 1 start date. If your OPT expires before October 1, a Cap-Gap extension automatically bridges your status if your petition is filed and selected in the lottery. Identifying and securing a Tiger Analytics offer well before the March registration window gives you the best chance of a clean transition.
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