ML Engineer Jobs at Tiger Analytics with Visa Sponsorship
Tiger Analytics hires ML Engineers to build and deploy production-grade models across data-intensive client engagements. The company sponsors work visas for this function, supporting candidates through H-1B, OPT, and other pathways, making it a practical target if you need sponsorship to work in the U.S.
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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.
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Get Access To All JobsTips for Finding ML Engineer Jobs at Tiger Analytics Jobs
Align your portfolio to client-facing ML work
Tiger Analytics delivers ML solutions to enterprise clients, so interviewers evaluate applied impact, not just model accuracy. Frame projects around business outcomes, such as reducing churn or improving forecast accuracy, not research metrics or academic benchmarks.
Confirm OPT STEM extension eligibility early
ML Engineer roles at Tiger Analytics typically qualify under CIP codes covered by the STEM OPT extension. Verify your degree classification with your DSO before accepting an offer so your 24-month extension timeline aligns with the employer's H-1B filing calendar.
Target Tiger Analytics roles using Migrate Mate
Search for ML Engineer openings at Tiger Analytics on Migrate Mate, which filters specifically for visa-sponsoring employers. You can confirm which visa types the company files for this role before spending time on the application.
Ask about the H-1B filing window during offer negotiation
USCIS H-1B cap registrations open in March for an October 1 start date. If you receive an offer outside that window, clarify with your recruiter whether Tiger Analytics will hold your start date or bridge you on OPT until the next filing cycle.
Prepare for DOL prevailing wage scrutiny on your LCA
Tiger Analytics submits a Labor Condition Application to DOL before filing your H-1B petition. The LCA locks in your worksite and wage level, so confirm your assigned project location matches what your employer intends to certify, especially if you will be working at a client site.
Gather evidence linking your degree to the ML Engineer role
USCIS requires specialty occupation documentation for H-1B approval. Collect transcripts, course descriptions, and any graduate coursework in machine learning, statistics, or computer science that directly maps to the responsibilities listed in your offer letter.
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Find ML Engineer at Tiger Analytics JobsFrequently Asked Questions
Does Tiger Analytics sponsor H-1B visas for ML Engineers?
Yes, Tiger Analytics sponsors H-1B visas for ML Engineer roles. The company participates in the annual USCIS H-1B cap registration process, so timing matters. If you receive an offer outside the March registration window, ask your recruiter how the company handles bridge arrangements for candidates on OPT or other valid status.
How do I apply for ML Engineer jobs at Tiger Analytics?
You can browse current ML Engineer openings at Tiger Analytics on Migrate Mate, which surfaces roles specifically tagged for visa sponsorship. Review the job descriptions carefully, as Tiger Analytics typically specifies whether the role involves client delivery work or internal platform development, which affects how you should frame your application and interview preparation.
Which visa types does Tiger Analytics commonly use for ML Engineers?
Tiger Analytics sponsors H-1B visas for experienced ML Engineers and supports F-1 OPT and CPT for students and recent graduates entering the role. The company also files EB-2 and EB-3 immigrant visa petitions, which can lead to a Green Card. TN visa sponsorship is available for qualified Canadian and Mexican nationals in this function.
What qualifications does Tiger Analytics expect for ML Engineer roles?
Tiger Analytics generally looks for a bachelor's or master's degree in computer science, statistics, or a related quantitative field, combined with hands-on experience building and deploying models in production environments. Proficiency in Python, familiarity with cloud ML infrastructure, and experience with real-world datasets from industries like retail, financial services, or healthcare strengthens your candidacy significantly.
How do I plan my timeline if I need visa sponsorship for an ML Engineer role at Tiger Analytics?
If you are on F-1 OPT, the critical deadline is the H-1B cap registration in March. You need an approved offer by then so Tiger Analytics can include you in the lottery. USCIS issues registration results in late March, with employment start dates no earlier than October 1. Build your job search timeline backward from March to give yourself adequate runway.
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