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Open nowPosted 445 days ago

Senior Machine Learning Engineer

Raspberry AI9 open roles

Where
United States
Work mode
Remote
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Your applicationOpen nowSenior Machine Learning EngineerRaspberry AI · United States

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Raspberry AI's own form.

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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. Raspberry AI postings stay open a median of 62 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 445 days ago

Raspberry AI median: 62 days open

The posting

RASPBERRY AI

Raspberry AI is a leading provider of industry-defining AI design software for fashion brands and retailers. Our software empowers brands to rapidly understand consumer demand and create unique designs within minutes. Leveraging cutting-edge AI analytics and generative AI capabilities, we help fashion brands revolutionize their design and merchandising processes.

We are a Series A startup, backed by top-tier venture capital firms such as Andreessen Horowitz, Khosla Ventures, MVP and Greycroft.

ABOUT THE ROLE

This is a full-time remote role for a Senior Machine Learning Engineer at Raspberry AI. We are seeking a highly talented and motivated Machine Learning Engineer to join our growing ML team. In this role, you will focus on improving the quality and performance of our cutting-edge diffusion models, pushing the boundaries of generative AI in the fashion domain.

Additional responsibilities may be assigned as business needs evolve.

RESPONSIBILITIES

- Conduct applied research and experimentation on state-of-the-art diffusion model architectures and training techniques.

- Implement and evaluate novel techniques for improving quality and controllability in generated designs.

- Analyze and interpret experimental results, draw meaningful conclusions, and communicate findings effectively.

- Collaborate closely with the team to translate prototypes into production-ready systems.

- Stay abreast of the latest advancements in diffusion models, deep learning, and generative AI research.

REQUIREMENTS

- Master's or Ph.D. in Computer Science, Machine Learning, or a related field. 3+ years of industry experience.

- Strong theoretical and practical understanding of deep learning, with a focus on generative models (e.g., GANs, VAEs, Diffusion Models).

- Hands-on experience with deep learning frameworks such as PyTorch.

- Experience with training and evaluating generative models on cloud GPU platforms (e.g., AWS, GCP, Azure).

- Proficiency in using and tuning multimodal LLMs, including experience with both API-based and open-source model implementations.

- Ability to effectively present complex technical information to both technical and non-technical audiences.

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