Senior Software Engineer, AI Science - Alembic

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.