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EXL

AI/ML Engineer

Pay: $100,000–$140,000/yr

Posted: 2 days ago

Location: Jersey City, NJ (Onsite)

Last Updated: 19 hours ago

Hours: Full-Time

Expires: 10/3/2026

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What they do

A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.

$130,801 / year median in New Jersey

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Job Description

We have requirement for 1 Senior Data Scientist / AI-ML Engineer and are looking for candidates with 6+ years of relevant experience

Base Compensation Range:

100,000 - 140,000 The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process. For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits Bachelor's in Computer science, engineering or any related field Key Requirements Strong hands-on expertise in AI/ML, Data Science, Python, SQL, and Git/GitHub . Proven experience building end-to-end data science and predictive modeling solutions , from problem definition through deployment. Strong understanding of Property & Casualty (P&C) Insurance business processes. Ability to translate complex business challenges into practical AI/ML and analytical solutions . Strong focus on business outcomes and measurable impact , beyond model development. Experience applying AI/ML solutions in areas such as: Pricing Risk Segmentation Underwriting Decision Support Forecasting Operational Optimization Strong GitHub and software engineering practices including: Version Control Code Reviews Documentation Testing Reusable Code Development Excellent communication skills with the ability to present technical concepts to business and non-technical stakeholders . Ability to work as a senior independent contributor , driving initiatives end-to-end with minimal support.

Experience leading:

Business Discovery Data Assessment Model Development & Validation Deployment User Adoption