Senior Engineer, Machine Learning

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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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.

Schedule

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Weekend work

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Assessment

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Deadline

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About this role

Senior Engineer, Machine Learning Bengaluru, KA, India Company Description: SanDisk is a leading global provider of flash memory and solid‑state storage solutions , designing and manufacturing products such as SSDs, memory cards, and USB flash drives for consumer, mobile, and enterprise applications. Founded in 1988 , the company has been a pioneer in flash technology, including the creation of the first flash‑based SSD in 1991 . Formerly part of Western Digital (2016-2025), SanDisk re‑emerged as an independent publicly traded company in 2025 , strengthening its focus on next‑generation storage technologies. It remains one of the world's largest suppliers of NAND flash memory Job Description: Role Overview We are looking for a highly skilled Machine Learning Engineer who can design, build, and own end-to-end ML systems in production. This role requires a strong blend of machine learning expertise, backend engineering, and full-stack development, with a focus on building reliable, scalable platforms used by leadership and critical business functions. Key Responsibilities Design, develop, and maintain end-to-end machine learning pipelines , including data ingestion, training, evaluation, deployment, monitoring, and retraining. Build and own production-grade ML services that are reliable, scalable, and fault-tolerant. Architect and manage async workflows and API-driven systems for ML and data services. Integrate ML solutions into complex production environments and distributed systems. Design robust systems with a strong focus on failure modes, observability, and guardrails to ensure reliability. Develop internal analytical tools used by leadership and cross-functional teams for decision-making. Develop interactive internal ML tools and dashboards using Streamlit for

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