Machine Learning Engineer - Search
To see similar active jobs please follow this link: Remote Development jobs
Role Description
At Dropbox, our pursuit of excellence in Machine Learning and Artificial Intelligence fuels our mission to empower users worldwide. We've cultivated a culture rooted in meticulous attention to detail, unwavering commitment to reliability, and a drive to innovate at scale.
As a Machine Leaning Engineer focused on search quality, you will play a crucial role in developing and enhancing our search capabilities to provide users with the best possible search experience. You will work on designing, coding, training, testing, deploying, and iterating on large-scale machine learning systems that drive the core functionalities of Dropbox Dash’s search features.
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.
Please note, Dropbox is currently only authorized to hire candidates from the following provinces: Alberta, British Columbia, Ontario, and Saskatchewan.
Responsibilities
You will work within the Machine Learning Team to design, code, train, test, deploy and iterate on large scale machine learning systems
You will build delightful products and experiences, while working alongside an excellent, multi-functional team across Engineering, Product and Design
You will help craft the direction of machine learning and artificial intelligence at Dropbox
Develop and maintain production-quality code for serving machine learning models at scale
Design online and offline ML experiments, perform data analysis, and explore feature quality for ML models
Communicate technical trade-offs to multidisciplinary stakeholders, including product managers, software developers, and business leaders
Proactively explore and integrate the latest advancements in Machine Learning into Dropbox's products
Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.
Requirements
BS, MS, or PhD in Computer Science or related technical field involving Machine Learning, or equivalent technical experience
5+ years of experience building production search or recommendation machine learning systems
Proven software engineering skills across multiple languages including but not limited to Python and Go
Familiarity with scalable search systems (e.g. ElasticSearch, OpenSearch, Lucene) and information retrieval algorithms (e.g. TF-IDF, BM25, Learning to Rank)
Experience with machine learning software packages (e.g., scikit-learn, TensorFlow, PyTorch), and related libraries (numpy, pandas)
Experience designing high-impact features for search or recommendation systems and developing, supporting, and debugging feature generation ETL pipelines
Strong analytical, problem-solving, and communication skills
Total Rewards
About the job
Machine Learning Engineer - Search
To see similar active jobs please follow this link: Remote Development jobs
Role Description
At Dropbox, our pursuit of excellence in Machine Learning and Artificial Intelligence fuels our mission to empower users worldwide. We've cultivated a culture rooted in meticulous attention to detail, unwavering commitment to reliability, and a drive to innovate at scale.
As a Machine Leaning Engineer focused on search quality, you will play a crucial role in developing and enhancing our search capabilities to provide users with the best possible search experience. You will work on designing, coding, training, testing, deploying, and iterating on large-scale machine learning systems that drive the core functionalities of Dropbox Dash’s search features.
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.
Please note, Dropbox is currently only authorized to hire candidates from the following provinces: Alberta, British Columbia, Ontario, and Saskatchewan.
Responsibilities
You will work within the Machine Learning Team to design, code, train, test, deploy and iterate on large scale machine learning systems
You will build delightful products and experiences, while working alongside an excellent, multi-functional team across Engineering, Product and Design
You will help craft the direction of machine learning and artificial intelligence at Dropbox
Develop and maintain production-quality code for serving machine learning models at scale
Design online and offline ML experiments, perform data analysis, and explore feature quality for ML models
Communicate technical trade-offs to multidisciplinary stakeholders, including product managers, software developers, and business leaders
Proactively explore and integrate the latest advancements in Machine Learning into Dropbox's products
Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.
Requirements
BS, MS, or PhD in Computer Science or related technical field involving Machine Learning, or equivalent technical experience
5+ years of experience building production search or recommendation machine learning systems
Proven software engineering skills across multiple languages including but not limited to Python and Go
Familiarity with scalable search systems (e.g. ElasticSearch, OpenSearch, Lucene) and information retrieval algorithms (e.g. TF-IDF, BM25, Learning to Rank)
Experience with machine learning software packages (e.g., scikit-learn, TensorFlow, PyTorch), and related libraries (numpy, pandas)
Experience designing high-impact features for search or recommendation systems and developing, supporting, and debugging feature generation ETL pipelines
Strong analytical, problem-solving, and communication skills