Staff or Sr. Software Engineer, ML Platform

About the Role

Key Responsibilities

• Develop software across the ML ops stack (e.g., data ingestion / processing, management of ML models, expand experimentation capabilities, etc.)
• Brainstorm with ML, infrastructure, and product engineers to deliver highly efficient and robust capabilities around creating and delivering ML models.
• Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
• Support in the creation and management of ML features.
• Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.
• Assist our skilled support team and operations team in triaging and resolving production issues.
• Mentor other engineers and deeply review code.
• Improve engineering standards, tooling, and processes.

Requirements

• Experience with functional or imperative programming languages: PHP, Python, Ruby, Go, C, Scala or Java.
• Experience building big data processing pipelines with tools like Apache Spark, Hadoop, PySpark, SQL, etc.
• Experience orchestrating complex data ingestion and processing pipelines with tools like Airflow, Dagster, or Luigi.
• Have built large-scale, distributed, production ML/AI systems or other ML Ops systems professionally and can point to things you've worked on.
• An analytical and data driven mindset, and know how to measure success with complicated ML/AI products.
• Put machine learning models or other data-derived artifacts into production at scale.
• Led technical architecture discussions and helped drive technical decisions within the team.
• The ability to write understandable, testable code with an eye towards maintainability.
• Strong communication skills and the capability to explain complex technical concepts to designers, support, and other specialists.
• Strong computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval.

Nice to Have

• Experience with data orchestration tools like Airflow, Dagster, or Luigi.
• Experience with large-scale distributed ML/AI systems.

Qualifications

• Professional experience building big data processing pipelines and ML/AI systems
• Experience with programming languages such as PHP, Python, Ruby, Go, C, Scala, or Java
• Experience with data orchestration and processing tools like Airflow, Dagster, Luigi
• Experience deploying ML models at scale

Benefits & Perks

• Time off programs
• Medical, dental, vision, mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program
• Additional details available at https://www.salesforcebenefits.com