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About this Role
As a Software engineer AI retrieval you will be responsible for designing implementing and optimizing the AI retrieval systems that power our platform. Youll work closely with our data scientists product managers and other engineers to ensure that our AI models are integrated seamlessly into our applications providing fast and accurate results. This role requires a deep understanding of software engineering principles and a strong foundation in AI and machine learning.
Design and implement AI retrieval systems: Develop and maintain the core AI retrieval algorithms and services that enable our platform to efficiently search and retrieve relevant content.
Optimize performance: Ensure that our AI retrieval systems are highly performant scalable and can handle large volumes of data and requests.
Collaborate with crossfunctional teams: Work closely with data scientists product managers and other engineers to understand requirements provide technical guidance and deliver highquality solutions.
Code quality and best practices: Write clean maintainable and welldocumented code adhering to best practices in software engineering.
Testing and validation: Develop comprehensive unit and integration tests to ensure the reliability and accuracy of our AI retrieval systems.
API development: Build and maintain REST and GraphQL APIs using frameworks like FastAPI and Flask to expose our AI retrieval capabilities to other services and applications.
Streaming and cancelable endpoints: Implement streaming responses and cancelable endpoints to support realtime and interactive use cases such as model output.
Continuous improvement: Stay uptodate with the latest developments in AI and software engineering and continuously improve our systems and processes.
Language fundamentals: Proficient in Python with a strong understanding of data types string manipulation type casting and conversions.
Functions: Experienced in calling functions using default and variable arguments and writing lambda functions.
Virtual environments: Familiar with tools like venv virtualenv pipenv and poetry for managing project dependencies.
File handling: Skilled in reading writing and manipulating files in Python.
Error Handling: Expert in handling errors and exceptions to ensure robust and reliable code.
Datamodels: Knowledgeable in designing and using data models to represent and manage data efficiently.
Context managers and logging best practices: Proficient in using context managers and implementing logging best practices to maintain code clarity and traceability.
Inheritance and method overriding: Experienced with objectoriented programming concepts including inheritance and method overriding.
Magic methods: Familiar with Pythons magic methods to enhance the functionality of custom classes.
Code formatting: Adheres to code formatting standards using tools like black isort flake8 and pylint.
Testing: Strong background in testing methodologies including unit testing with pytest mocking and integration testing.
Versioning: Familiar with semantic versioning and maintaining changelogs to track changes and updates.
Data structures: Proficient in using stack queue and priority queue data structures (via collections) to manage and process data efficiently.
Functional programming: Experienced in functional programming concepts such as map filter reduce generators and decorators.
Async programming: Skilled in asynchronous programming using asyncio aiohttp async generators and handling timeouts with waitfor.
Threading vs multiprocessing: Understands the differences and tradeoffs between threading and multiprocessing and can choose the appropriate approach for different tasks.
Memory and performance profiling: Proficient in using tools like tracemalloc and cProfile to identify and optimize memory usage and performance bottlenecks.
API development: Experienced in developing and maintaining REST and GraphQL APIs using frameworks like FastAPI and Flask.
Streaming responses and cancelable endpoints: Capable of implementing streaming responses and cancelable endpoints to support realtime and interactive use cases.
Machine learning experience: Familiarity with machine learning frameworks and libraries such as TensorFlow PyTorch or scikitlearn.
Natural Language Processing (NLP): Experience with NLP techniques and tools such as spaCy or NLTK.
Distributed systems: Knowledge of distributed systems and experience with tools like Kubernetes or Docker.
Cloud services: Experience with cloud platforms like AWS GCP or Azure.
Open source contributions: Contributions to opensource projects or a strong portfolio of personal projects.
Benefits & perks (US Fulltime employees)
Generous PTO plus company holidays
Medical dental and vision coverage for you and your family
Paid parental leave for all parents (12 weeks)
Fertility and family planning support
Earlydetection cancer testing through Galleri
Flexible spending account and dependent FSA options
Health savings account for eligible plans with company contribution
Annual worklife stipends for:
Home office setup cell phone internet
Wellness stipend for gym massage/chiropractor personal training etc.
Learning and development stipend
Companywide offsites and team offsites
Competitive compensation company stock options and 401k
Writer is an equalopportunity employer and is committed to diversity. We dont make hiring or employment decisions based on race color religion creed gender national origin age disability veteran status marital status pregnancy sex gender expression or identity sexual orientation citizenship or any other basis protected by applicable local state or federal law. Under the San Francisco Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.
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Full-Time