Tiger Analytics Inc.
Machine Learning Engineer
Remote role where the employee must remain based in a particular country.
United States only
Employer listed it 10 months ago · Found 1h ago
Been open since 10 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
Not stated
Location
United States only
Timezone
US East
Contract
Full-time
Experience
Mid
Category
Data
This employer didn't state pay. Jobs like this usually pay around $110k–$205k a year, a typical range taken from 231 mid-level data roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Work from home
This is a remote role, but the employee must be based in United States. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "United States, Remote"
What Nomaders makes of it
- Residency required in United States
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
Tiger Analytics is a global leader in AI and advanced analytics consulting, empowering Fortune 1000 companies to solve their toughest business challenges. We are on a mission to push the boundaries of what AI can do, providing data-driven certainty for a better tomorrow. Our diverse team of over 6,000 technologists and consultants operates across five continents, building cutting-edge ML and data solutions at scale. Join us to do great work and shape the future of enterprise AI.
Requirements
5+ years of professional software development experience, with strong proficiency in Python, and applying software engineering and design principles (OOP, functional programming, design patterns, testing frameworks, CI/CD fundamentals).
Deep understanding of cloud-based data platforms (Azure, Databricks etc.), including cluster configuration, Spark optimization techniques and best practices.
Strong understanding of distributed data processing systems (Spark, Delta tables, cloud storage layers) with hands-on experience in building data pipelines, optimizing performance, and handling large-scale datasets.
Exposure to DevOps and engineering hygiene practices such as containerization (Docker), infrastructure-as-code, CI/CD pipelines, and automated testing for workflows.
Proven ability to work effectively in cross-functional teams (DS, DE, Cloud Ops, Product) with a proactive, inquisitive, and go-getter mindset
Ability to translate ambiguous business or analytical requirements into scalable technical solutions, with solid grounding in code quality, reliability, observability, and engineering best practices.
Additional qualifications (Nice to have):
Experience in operationalizing and deploying machine learning models using production-grade MLOps frameworks (MLflow, AzureML, Databricks Model Serving), with a strong understanding of model lifecycle management such as versioning, lineage, monitoring, retraining workflows, and deployment automation.
Familiarity with modern data and ML architecture patterns such as feature stores, vector stores, low-latency inference pipelines.
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.
Requirements
- ·Deep understanding of cloud-based data platforms (Azure, Databricks etc.), including cluster configuration, Spark optimization techniques and best practices.
- ·Strong understanding of distributed data processing systems (Spark, Delta tables, cloud storage layers) with hands-on experience in building data pipelines, optimizing performance, and handling large-scale datasets.
- ·Exposure to DevOps and engineering hygiene practices such as containerization (Docker), infrastructure-as-code, CI/CD pipelines, and automated testing for workflows.
- ·Proven ability to work effectively in cross-functional teams (DS, DE, Cloud Ops, Product) with a proactive, inquisitive, and go-getter mindset
- ·Ability to translate ambiguous business or analytical requirements into scalable technical solutions, with solid grounding in code quality, reliability, observability, and engineering best practices.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at Tiger Analytics Inc., mentioning your remote working experience and working hours (US East).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1h ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
Similar roles
Other open data roles with comparable remote rules.
Free to apply, no account needed.
Typically $110k to $205k per year · You'll be taken to the employer's careers page.