Member of Technical Staff (Machine Learning Engineer)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• 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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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

Staff Plus From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Early From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Member of Technical Staff (Machine Learning Engineer) Remote What You'll Do - Translate cutting-edge research into production-ready machine learning systems - Design, build, and deploy end-to-end ML models and pipelines - Develop and optimize models for image and video processing - Own the full ML lifecycle: experimentation, training/fine-tuning, evaluation, and deployment - Rapidly prototype using open-source models and adapt them for product needs - Conduct experiments, analyze results, and iterate to improve performance - Collaborate with researchers and cross-functional teams (product, engineering, design) to deliver ML solutions at scale - Participate with advancements in machine learning and apply them to continuously improve products What We're Looking For Required Qualifications - MS/PhD in Computer Science, Electrical Engineering, or related field - Strong research experience with familiarity in top conferences (e.g., CVPR, ICCV, NeurIPS) - 5+ years of experience in Python and proficiency in Java, C++, or Scala - Strong understanding of diffusion models - Strong understanding of multi-threading and memory management - Solid knowledge of ML architectures: CNNs and Transformers - Experience with PyTorch or TensorFlow - Experience building end-to-end ML deployment and inference systems, especially for low-latency, real-time applications - Experience deploying ML models in cloud environments (AWS preferred) - Experience with experiment tracking systems and ML workflows Nice to Have - Experience in low level optimisation, cuda etc. - Experience productionizing and scaling ML models in real-world systems - Contributions to open-source projects - Experience with MLOps tools or distributed training systems - Familiarity with relational databases (Postgres/MySQL) -

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