Software Engineer, Machine Learning​/ ML Engineer, Cloud Engineer - Software

Software Engineer

Location:

Onsite Candidates may be based in either the San Francisco Bay Area or the Des Moines Metro Area 6 Months Description

We are seeking a highly technical and self-directed Senior Software Engineer to contribute to the development of data processing pipelines for a new AI-enabled data analytics product targeted at Large Ag customers.

• 5+ years of professional software development experience using Python
• 2+ years of hands-on experience with AWS and Databricks in production environments

We are looking for mid-career professionals with a proven track record of deploying cloud-native solutions in fast-paced software delivery environments.

• Strong communication skills, with the ability to clearly articulate technical concepts to both technical and non-technical stakeholders (this is extremely important - please vet out accorrdingly)
• The ability to work effectively with limited supervision in a distributed team environment
• A proactive mindset, adaptability, and a commitment to team success

• Design and implement AWS/Databricks solutions to process large geospatial datasets for real-time API services
• Develop and maintain REST APIs and backend processes using AWS Lambda
• Build infrastructure as code using Terraform
• Set up and maintain CI/CD pipelines using Git Hub Actions
• Optimize system performance and workflows to improve scalability and reduce cloud costs
• Enhance monitoring and alerting across systems using Datadog
• Support field testing and customer operations by debugging and resolving data issues
• Collaborate with product managers and end users to understand requirements, build backlog, and prioritize work
• Work closely with data scientists to product ionize prototypes and proof-of-concept models

• Excellent coding skills in Python with experience deploying production-grade software
• Strong foundation in test-driven development
• Solid understanding of cloud computing, especially AWS services such as IAM, Lambda, S3, RDS
• Professional experience building Databricks workflows and optimizing PySpark queries

• Experience working with geospatial data and related libraries/tools
• Experience building and operating API using AWS lambda
• Familiarity with data lake architectures and Delta Lake
• Experience with event-driven architectures and streaming data pipelines (e.g., Kafka, Kinesis)
• Exposure to ML Ops or deploying machine learning models in production
• Prior experience in cross‑functional teams involving product, data science, and backend engineering teams