Gen AI Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Gen AI Engineer In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below: • Develop data preparation tasks, while identifying patterns or anomalies. • Ensure data readiness for advanced modeling. • Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions. • Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices. • Design and develop predictive models and data-driven analyses to address business challenges. • Build, evaluate, and deploy models, standardize code, and contribute to knowledge management. • Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions. • Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance. • Proactively maintain models and implement improvements for accuracy and reliability. • Apply governance controls to mitigate risks and ensure compliance. • Analyze performance trends, recommend improvements, and document discrepancies for escalation. • Maintain comprehensive documentation standards, while participating in knowledge transfer sessions. • Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models. • Apply the predefined quality measurement framework at an individual task level in the project. • Deploy complex analytics tools or multi-system integration, while validating deployment success. • Participate in developing scripts or templates for repeated deployments tasks.

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