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Job Highlights

AI-extracted key information

This remote opportunity at Dropbox as a Machine Learning Engineer allows professionals transitioning from traditional roles to engage in cutting-edge AI projects while collaborating with a top-tier team. It offers a chance to impact millions of users and shape innovative experiences in a fully remote setting.

Experience Level

Senior Level (5-10 years)

Education Requirements

Bachelor's degree

AI-powered analysis • Data extracted from job description
Dropbox logo

Machine Learning Engineer, Dash

DropboxRemote - GermanyEngineering & Technical

Posted 1 months ago

Full-Time

Employment Type

Remote

Work Location

About This Role

Role Description

As a Machine Leaning Engineer on our Multimedia AI team, you will be involved in shaping the future direction of Dropbox Dash and pushing the boundaries on what the world thinks is possible by leveraging the latest advancements in

AI/

ML. You will join a team of top-tier Machine Learning Engineers and be an inherent part of the product org to create and build delightful new experiences.

Collaborating closely with cross-functional teams, you'll leverage your

ML

expertise to tackle audacious challenges. Your contributions will directly impact millions of users, as every line of code you write furthers our mission to revolutionize the way people work and collaborate.

Our Engineering Career Framework is

viewable by anyone outside the company

and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more

here

.

Responsibilities

​​Work with large scale data systems, and infrastructure

Help productionize multimodal and semantic retrieval systems at scale, powering Dash’s multimedia and creative search experiences.

​​Partner with product, design, and infrastructure teams to improve retrieval, ranking, and conversational experiences across image, video, and text content.

​​Build and iterate on quick prototypes and experimental features, driving innovation in multimodal interaction and creative workflows.

​​Run quality and performance benchmarks across individual components and end-to-end systems to identify optimization opportunities.

​​Contribute to open source projects and leverage OSS tools for efficient inference and scaling.

On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.

Requirements

BS, MS, or PhD in Computer Science

, Mathematics, Statistics, or other quantitative fields

or

related

work

Experience

5

+ years of experience

in engineering

with 3+ years

of experience

building

M

achine

L

earning or AI systems

Proven software engineering skills across multiple languages including but not limited to Python,

Go,

C/C++

Experience With

M

achine

L

earning software

tools and libraries

(e.g.,

Py

Torch

,

HuggingFace

,

TensorFlow,

Keras

,

S

cikit-learn,

etc.

)

​​Familiarity with search-related applications of Large Language Models

Proven experience in machine learning, multimodal AI, or search and ranking systems.

Familiarity with semantic search, embeddings, vector retrieval, and optimizing ranking metrics such as nDCG or MRR.

Experience running quality and performance benchmarks across components and end-to-end pipelines in large-scale machine learning and retrieval systems to identify and drive optimizations.

Preferred Qualifications

PhD in Computer Science or related field with research in machine learning

Experience With One Or More Of The Following: Natural Language Processing, Deep Learning, Bayesian Reasoning

,

recommend

er

systems, learning

to rank

, speech processing, learning from semistructured data,

graph learning,

reinforcement or active learning,

large language models,

ML software systems,

r

etrieval-augmented generation

,

machine learning on e

dge

devices

Experience Building 0→1 Ml Products At Large

(dropbox-level)

scale or multiple 0→1 products at smaller scale including experience with large-scale product systems

Compensation

Germany Pay Range

€118.200

€159.900 EUR

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