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AshbyHQ
Posted 138 days agoVerified live 2d ago

Machine Learning Researcher

Brief overview

New JerseyIn-person
UndergradOr in progress
12 H-1B approvalsDept. of Labor
5 green cardsCertified filings
Machine learningDeep learningPython programmingTime series forecastingNatural language processing (NLP)End-to-end data processingModel prototyping and optimizationResearch and model iteration

About the company

A technology startup providing recruitment and people operations support.

Visa sponsorship history

4 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
12H-1B approved
100%approval rate
2new H-1B hires
5PERM certified
$160,000median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
20231
20244
20256
20261
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20231
20242
20251
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
20232
20243
Top sponsored roles
Quantitative ResearcherQuant EngineerFinancial Analyst
Sponsored employees from
China

Job description

Key Responsibilities:

1. Mine alpha factors and build predictive models via deep learning based on multi-dimensional financial market data.

2. Explore signal fusion and strategy ensemble approaches to enhance model robustness and portfolio return characteristics.

3. Rapidly prototype, reproduce and optimize state-of-the-art deep learning models with mainstream ML frameworks.

4. Stay updated on latest academic and industrial research, conduct ongoing model iteration and performance enhancement.

Qualifications:

1. Bachelor’s degree or above from top domestic and international universities, majoring in Computer Science, Mathematics, Statistics, Machine Learning or related quantitative disciplines.

2. Strong theoretical foundation in machine learning, proficient in Python and mainstream deep learning frameworks; capable of end-to-end data processing and independent modeling.

3. Hands-on research or project experience in time series forecasting, NLP or other deep learning related domains.

4. Logical, rigorous mindset with excellent self-learning capability and strong interest in applying ML to quantitative finance.

5. Prior internship or working experience in Internet, AI, fintech or quantitative domains.

Preferred Qualifications:1. Kaggle competition awards or first-author publications at top ML conferences (NeurIPS / ICML / ICLR).2. Relevant internship experience in quantitative trading, asset management or financial technology.

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