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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
Machine Learning Engineer, Dash
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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