Senior Machine Learning Engineer - Hybrid

Senior Machine Learning Engineer | AI/Healthcare | $180K-$240K

Jersey City, NJ or Los Angeles, CA | Hybrid | Full-Time

We're working with a fast-growing technology company in the

AI and healthcare space

that's looking to add a Senior Machine Learning Engineer to its growing engineering team.

This is a hands-on role focused on building machine learning models that directly power a production platform and influence real-world decision-making. You'll own models throughout the lifecycle, from experimentation and feature engineering through evaluation, deployment, and production monitoring.

You'll work with complex, large-scale datasets and partner closely with engineering, data, and domain experts to develop models that are accurate, reliable, explainable, and ready for real-world use.

What You'll Do

• Design, train, evaluate, and improve

production machine learning models

• Perform feature engineering across

time-series, sequential, and structured data

• Own model development from experimentation through production
• Build evaluation frameworks, backtesting systems, and model regression tests
• Develop approaches for noisy or imperfect labels and ground truth
• Evaluate model performance across metrics including calibration, sensitivity, specificity, and class imbalance
• Identify and prevent issues such as

temporal leakage and model degradation

• Analyze model robustness and performance across different populations and environments
• Partner with domain experts to define prediction targets and appropriate evaluation criteria
• Work closely with ML infrastructure and engineering teams on deployment and serving
• Monitor model performance in production and identify opportunities for improvement
• Clearly communicate model behavior, tradeoffs, and limitations to technical and non-technical stakeholders

What You Need

• 5+ years of experience building

machine learning models that have reached production

• Strong

Python

• Experience with modern

deep learning frameworks

• Strong understanding of classical machine learning techniques
• Experience working with

time-series or sequential data

• Strong model evaluation experience, including

calibration, class imbalance, and temporal leakage

• Experience building evaluation, backtesting, or model regression infrastructure
• Strong

SQL

and experience working with production datasets

• Experience owning models beyond experimentation and into real-world production use
• Ability to communicate complex model behavior and limitations to non-technical stakeholders
• Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related technical field
• Ability to work onsite in

Jersey City, NJ at least 3 days per week

Nice to Have

• Experience building ML systems in

healthcare or another regulated industry

• Experience with physiological, sensor, clinical, or other complex time-series data
• Experience with predictive modeling or early-warning systems
• Experience with model validation in highly regulated environments
• Experience performing subgroup, bias, or robustness analysis
• Research publications, significant open-source contributions, or a strong research or engineering background
• Startup or high-growth technology company experience

Compensation & Benefits

$180,000-$240,000 base salary + equity

• 100% company-paid medical, dental, and vision coverage
• 401(k) with company match
• Generous PTO
• Commuter stipend

Benefits

Email Your Resume In Word To

Taylor.McAlister@CyberCoders.com

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Taylor McAlister - Sr. Executive Recruiter

For this position, you must be currently authorized to work in the United States without the need for sponsorship for a non-immigrant visa. This is a new role.

CyberCoders will consider for Employment in the City of Los Angeles qualified Applicants with Criminal Histories in a manner consistent with the requirements of the Los Angeles Fair Chance Initiative for Hiring (Ban the Box) Ordinance.

This job was first posted by CyberCoders on 10/29/2026 and applications will be accepted on an ongoing basis until the position is filled or closed.

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, ancestry, citizenship, genetic information, registered domestic partner status, marital status, status as a crime victim, disability, protected veteran status, or any other characteristic protected by law.

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