Solution Engineer II (AI/ML lead)

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

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

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

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered Verified - SEC 10-K source checked Jun 20, 2026

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

Solution Engineer II (AI/ML lead) Noida, India Position: Solution Engineer II (AI/ML lead) Job Description: Principal Accountabilities Collaborate with teams to translate business requirements into technical specifications, system architecture, and ML pipelines. Drive end-to-end solution delivery - including data preparation, model development, optimization, validation, deployment, and continuous improvement. Provide technical guidance and mentorship to junior engineers and data scientists; review and refine their designs and code implementations. Develop reusable ML frameworks, model training workflows, and inference pipelines for rapid prototyping and deployment. Evaluate and integrate state-of-the-art AI/ML technologies to continuously improve model efficiency and system design. Respond to client RFQs and provide robust technical proposals and solution architectures. Partner cross-functionally with system engineers, embedded developers, and application teams for integrated AI system delivery. Job Complexity & Impact Demonstrates expert-level depth across machine learning, system integration, and model optimization. Mentors ML teams with minimal supervision. Defines best practices for AI model lifecycle management and process improvements. Solves complex problems by combining innovative and existing methods to deliver production-grade AI solutions. Represents the level at which career may stabilize for many years or even until retirement Work Responsibilities Mentor 2-5 member AI engineering team for full-cycle ML product development. Architect, implement, and optimize AI models for edge computing platforms ensuring high throughput, accuracy and low latency. Develop and benchmark AI model pipelines on NVIDIA Jetson (Nano & Xavier), Qualcomm Snapdragon 835 and i.MX8 platforms or any other constrained platform. To work on platforms like Snapdragon Neural Processing Engine (SNPE), FastCV, Halide, Deep

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