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Alembic Limited

Senior Software Engineer, AI Science

Alembic Limited, San Francisco, CA, United States


About the Role - Senior Software Engineer, AI Science

We are seeking a talented Senior Software Engineer to join our AI Science team -- our research arm. This role focuses on conducting groundbreaking research that advances the state-of-the-art in AI and machine learning. You will work on ambitious projects, collaborate with a dynamic team of researchers and engineers, and derive insights that push an industry forward.

Key Responsibilities:
  • Conduct Cutting-Edge Research: Engage in groundbreaking AI and machine learning research that pushes the boundaries of the field.
  • Innovate Algorithms: Develop and experiment with new algorithms, models, and approaches to solve complex problems.
  • Collaborate Across Teams: Work closely with cross-functional teams, including engineers, data scientists, and product managers to bring research ideas to life.
  • Stay Updated: Keep abreast of the latest developments in AI and ML and apply this knowledge to your work.
A strong foundation in these technologies will set you up for success:

Primary skills:
  • Python programming: Experience delivering production-ready python programs.
  • Relational databases: Experience in querying, designing and optimizing relational databases such as Postgres.
  • Software development lifecycle management: Experience owning projects end-to-end from scoping, designing, coding, release and continuous monitoring in production environment.
  • Capacity planning and management: Experience with profiling methods and scalability assessment.
  • Data processing: Experience with data preprocessing techniques such as cleaning, transformation, normalization, and feature extraction.
Secondary skills:
  • ELT pipeline: Experience with ELT pipeline and orchestration systems such as Airflow.
  • Database systems: Experience working with one of more of non-SQL databases such as Druid, Elasticsearch and neo4j.
  • AWS: Experience deploying and managing applications on AWS.
  • Containerization and Virtualization: Proficiency in Docker and experience with container management and deployment.
  • Statistics and mathematics: Understanding of statistical concepts and methods such as statistical testing, regression analysis, time series analysis, and probability theory.