Job Closed
This listing is no longer active.
Revolutionizing the Transportation of Goods
Senior Software Engineer – ML Training Infrastructure
Location
Pennsylvania
Posted
38 days ago
Salary
0
Seniority
Senior
Job Description
Senior Software Engineer – ML Training Infrastructure
Stack AV
• Provide a reliable, scalable, and easy to use training framework for modeling needs of Stack AV. • Build tools for testing, validation, and understanding models and the data used to train them. • Optimize and deploy models.
Job Requirements
- Experience with both ML Platforms and building ML-based applications.
- Experience building scalable, reliable infra at a fast-paced environment working with MLEs on several different modeling teams.
- A deep understanding of design tradeoffs and ability to articulate those tradeoffs and work with others on getting alignment.
- Experience with building ML models or ML infra in the domains of autonomous vehicles, perception, and decision making (desirable but not required).
- Experience with model training, model optimization, or large data processing pipelines.
- Built an end to end ML model pipeline including components such as logs processing, feature extraction, dataset storage, model configuration management, model training, experiment frameworks, and serving deployment.
- Shipped ML products (NLP, computer vision, recommender systems, etc.) at scale to make business impact.
- Knows how to build appropriate abstractions and tooling to ensure MLEs are able to rapidly iterate on models.
- Prior AV experience
Benefits
- Equal opportunity workplace
- Commitment to building a culture of inclusion, entrepreneurship, and innovation
Related Guides
Related Job Pages
More Full-stack Engineer Jobs
• Translate high-level architecture direction into scalable, maintainable software designs • Guide the engineering team to deliver high-quality, observable, and testable code aligned with product and architectural goals • Combine system design, engineering leadership, and operational ownership • Work closely with product, platform, and engineering teams
• Design the metadata models and schemas for APIs • Drive the technical API strategy for integrations • Design, build, and deploy strategic integrations • Collaborate with product teams to identify use cases • Act as the technical anchor for the team
Staff Software Engineer, AI Systems
FederatoWhen underwriters have real-time risk selection and portfolio insights at their fingertips, profitable growth follows!
• Design and implement agent workflows and orchestration systems for AI-powered product features • Build backend services that integrate LLMs with structured insurance data and platform APIs • Develop infrastructure for tooling, context management, and agent execution • Contribute to internal frameworks supporting prompt iteration, evaluation, and observability • Partner with product and design to translate underwriting workflows into AI-enabled product experiences • Help define architectural patterns for building reliable AI-native features in production • Work across backend systems, data infrastructure, and product integrations to ship user-facing capabilities
Full Stack Software Engineer – Data Observability, Operational Tooling
AccelerantWhere True Partnerships Exist
• Designing and building front-end interfaces for internal operational tooling, including dashboards, data observability views, and stakeholder communication surfaces • Developing rich data visualizations that surface pipeline health, data quality metrics, and business KPIs to technical and non-technical audiences • Building and maintaining backend services that support operational tooling, integrating with data infrastructure such as Snowflake, dbt, and monitoring platforms • Collaborating closely with data engineers, analytics engineers, and business stakeholders to translate data observability requirements into intuitive, high-quality interfaces • Working independently as a software engineer within a data-focused team, driving technical decisions for the tooling layer while leveraging other full stack teams across the organization for guidance and support • Shipping iteratively, balancing speed of delivery with code quality, maintainability, and scalability




