Responsibilities

• Design and implement AI retrieval systems:

  • Develop and maintain core AI retrieval algorithms and services for efficient content search and retrieval.

• Optimize performance:

  • Ensure high performance, scalability, and capability to handle large data volumes and requests.

• Collaborate with cross-functional teams:

  • Work with data scientists, product managers, and engineers to understand requirements and deliver high-quality solutions.

• Code quality and best practices:

  • Write clean, maintainable, and well-documented code, adhering to software engineering best practices.

• Testing and validation:

  • Develop comprehensive unit and integration tests to ensure reliability and accuracy of AI retrieval systems.

• API development:

  • Build and maintain REST and GraphQL APIs using frameworks like FastAPI and Flask.

• Streaming and cancelable endpoints:

  • Implement streaming responses and cancelable endpoints for real-time and interactive use cases.

• Continuous improvement:

  • Stay updated with the latest developments in AI and software engineering, continuously improving systems and processes.

Qualifications

• Language fundamentals: Proficient in Python, with 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.
• File handling: Skilled in reading, writing, and manipulating files in Python.
• Error handling: Expert in handling errors and exceptions for robust code.
• Data models: Knowledgeable in designing and using data models.
• Context managers and logging: Proficient in using context managers and implementing logging best practices.
• Object-oriented programming: Experienced with inheritance and method overriding.
• Magic methods: Familiar with Python's magic methods for custom classes.
• Code formatting: Adheres to standards using tools like black, isort, flake8, and pylint.
• Testing: Strong background in testing methodologies, including unit testing with pytest.
• Versioning: Familiar with semantic versioning and maintaining changelogs.
• Data structures: Proficient in stack, queue, and priority queue data structures.
• Functional programming: Experienced in concepts like map, filter, reduce, generators, and decorators.
• Async programming: Skilled in asynchronous programming using asyncio and aiohttp.
• Threading vs multiprocessing: Understands differences and trade-offs between threading and multiprocessing.
• Memory and performance profiling: Proficient in using tools like tracemalloc and cProfile.
• API development: Experienced in developing REST and GraphQL APIs.
• Streaming responses: Capable of implementing streaming responses and cancelable endpoints.

Preferred Skills and Experience

• Familiarity with machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
• Experience with Natural Language Processing (NLP) techniques and tools (spaCy, NLTK).
• Knowledge of distributed systems and experience with tools like Kubernetes or Docker.
• Experience with cloud platforms (AWS, GCP, Azure).
• Contributions to open-source projects or a strong portfolio of personal projects.

Benefits & Perks

• Generous PTO plus company holidays.
• Comprehensive medical and dental insurance.
• Paid parental leave for all parents (12 weeks).
• Fertility and family planning support.
• Early-detection cancer testing through Galleri.
• Competitive pension scheme and company contribution.
• Annual work-life stipends for:
  • Home office setup, cell phone, internet.
  • Wellness stipend for gym, massage/chiropractor, personal training, etc.
  • Learning and development stipend.
• Company-wide off-sites and team off-sites.
• Competitive compensation and company stock options.