Machine Learning, NLP London
Snapchat
Full Time
London
90000 - 95000 GBP ANNUAL Today
Job description
Snap Inc
is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat
, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio
, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles
.
The Cameos team is innovating new ways for Snapchatters to express themselves with their friends. With Cameos, you become the star of short, looping videos that you can customize with your own face and send to friends in Chat. The team consists of engineers, designers, and content specialists who are committed to creating the perfect Cameo for every moment.
We’re looking for a Machine Learning Engineer to join the Generative AI team at Snap Inc!
What you’ll do:
- Research the latest techniques and methods in deep learning and natural language processing to improve the dialog system across different use cases, including multimodal conversation, long-term memory, chitchat, intent recognition and others
- Work closely with stakeholders from product, engineering, content policy on a long-term improvement over the dialog system use cases, for both external release and internal use cases
- Introduce new techniques, tools, and architecture that improve the quality, performance, latency, throughput, and efficiency of our models
- Create products that are used by millions of Snapchatters
Knowledge, Skills & Abilities:
- Strong understanding of machine learning approaches and algorithms in natural language processing
- Ability to collect and analyze complex unstructured data
- Ability to proactively learn new concepts and apply them at work
- Strong communication and collaboration skills
Minimum Qualifications:
- BS in a related technical field such as computer science or equivalent years of experience
- 3+ years of industry machine learning experience
- Experience developing novel techniques for machine learning model measurement and mitigation
- Experience working with machine learning frameworks such as PyTorch and TensorFlow
Preferred Qualifications:
- Advanced degree in computer science (machine learning, NLP, deep learning) or another related area of study
- Strong track record of coming up with new ideas or improving upon existing ideas in machine learning demonstrated by accomplishments such as first author publications or projects
- Experience working on dialog systems, large language models or virtual assistants
- Experience in interdisciplinary research collaborations
- Experience in creating high-performance implementations of deep learning algorithms
- Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects
- Practical experience with Generative ML models for NLP or CV tasks
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets. If you have a disability or special need that requires accommodation, please don’t be shy and contact us at .
Our Benefits
Snapchat
https://www.snap.com
Santa Monica, United States
Evan Spiegel
Unknown / Non-Applicable
5001 to 10000 Employees
Company - Public
Computer Hardware Development
2011
