Senior AI Engineer

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November 13

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Hercules

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Transport

Hercules is an award-winning, asset-based motor carrier and customs brokerage, specializing in US-to-Canada and intra US shipments. The company offers services that combine the flexibility of a regional carrier with the national coverage, positioning them as one of the fastest-growing less-than-truckload (LTL) carriers in the market. Hercules operates over 1000 pieces of equipment through more than 30 terminals, boasting an innovative 'no breakbulk' structure that reduces transit time and minimizes the risk of damage and misrouting. Additionally, Hercules employs the latest green fleet technology in partnership with both the Canada Border Services Agency and US Customs and Border Protection, demonstrating a commitment to responsible and efficient transportation solutions.

201 - 500 employees

🚗 Transport

📋 Description

• Create training environments that elevate the quality ceiling of synthetic data, and provide high-quality reward signals for both off- and on-policy learning. • Design model behaviors that optimize for interpretability and an outstanding user experience. • Train agentic models that autonomously interact with complex structured and unstructured environments, write and prototype code, and navigate multimodal inputs. • Own benchmarking pipelines – assemble high-quality datasets and measure impact of different training parameters or methodologies. • Architect scalable inference strategies that maximize compute efficiency. • Maintain solutions to ensure stable, reliable execution for customers. • Closely collaborate with engineering team to design important intersections of AI and product services such as interfaces, inference tracking, checkpointing, data persistence and caching. • Contribute to engineering culture; mentor peers, evolve patterns, raise the bar on code quality, testing strategy, and documentation.

🎯 Requirements

• Strong background in both ML and engineering • Great communication skills and rapid understanding of problem descriptions • High agency; willing to propose, prototype and own solutions • Experience in post-training large models (SFT, distillation, RL) • Experience deploying models at production scale • Previous work with dockerized systems (Docker, Kubernetes, etc.) • Previous contributions to open research or AI infrastructure • Strong familiarity with latest AI research and open-source tooling • Experience shipping complex software and owning production-code • Nice to Have: Experience performance-engineering inference architecture for maximum throughput (vLLM, SGlang, llama.cpp) • Nice to Have: Detailed knowledge of RL frameworks (verifiers, ART, prime-rl, trl) • Nice to Have: Published models or blog posts/publications

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development