Lead the design and operation of production machine learning systems for batch and online use cases with a focus on reliability and scalability.
Build and improve ML lifecycle infrastructure including training pipelines, inference workflows, monitoring, and automation.
Partner with cross-functional teams to translate business problems into ML solutions and guide prototypes to robust production systems.
Included Health is a healthcare company delivering integrated virtual care and navigation, aiming to raise the standard of healthcare for everyone. They are a remote-first organization offering comprehensive benefits and fostering a culture of inclusion.
Own end-to-end ML system execution including data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
Architect scalable inference systems, balance latency, cost, and reliability, and deploy production-grade ML solutions.
Gina's Tech Jobs is a recruiting and staffing company that helps firms hire technical talent. They are a small agency focused on IT roles, fostering a high-trust, collaborative environment.
Develop and integrate ML, NLP, and Generative AI models to create smart collaborative solutions.
Build and optimize agentic workflows using LangChain, LangGraph, and similar frameworks.
Collaborate with engineering and product teams to deliver AI-driven features and prototype tools.
We are a technology company building next-generation AI-powered workplace assistants. Our team values innovation, engineering excellence, and continuous learning in an open and supportive environment.
Lead and scale a team building next-generation AI evaluation infrastructure.
Define strategy and roadmap for evaluation platform including benchmark design and quality monitoring.
Drive innovation in evaluation methodologies like agentic and multi-turn assessment.
ServiceNow is the AI control tower for business reinvention, helping 85% of the Fortune 500 work smarter. The company fosters an AI-native culture where technology and talent are unstoppable together.
Design and implement AI capabilities for intelligent data characterization and decision support.
Evaluate, optimize, and deploy open-weight foundation models for resource-constrained edge environments.
Develop efficient inference pipelines and implement RAG, semantic search, and model optimization techniques.
Expression provides data fusion, analytics, AI/ML, software engineering, and spectrum management solutions to the U.S. Department of Defense and national security community. Founded in 1997 and headquartered in Washington DC, the company was ranked #1 on Washington Technology's 2018 Fast 50 and is a Top 20 Big Data Solutions Provider, fostering a collaborative culture with opportunities for growth.
Build ML infrastructure for low-latency model deployment, distributed inference pipelines, and real-time telemetry.
Scale ranking systems by moving models from experimentation to production, optimizing latency and cost trade-offs.
Implement model CI/CD for automated versioning, canary releases, hot-swappable container rollouts, and zero-downtime rollbacks.
Sequen provides an integrated platform that pairs cutting-edge frontier ranking models with infrastructure to run them in production at sub-10ms latency and enterprise scale. They are a small, highly technical, early-stage team focused on turning recent AI advances into production-grade systems.
Own the offline dataset pipeline converting multi-sensor data into VLM/VLA training datasets.
Develop VLM-assisted auto-labeling with open-vocabulary detection and semantic enrichment.
Curate long-tail scenarios to measurably improve downstream model performance.
Torc develops autonomous driving software for trucks to transform freight movement. As a pioneer in autonomous technology since 2007 and now part of Daimler, we foster a collaborative, energetic, and team-focused culture.
Lead technical discovery with foundation model labs, frontier AI teams, and large enterprises to understand model objectives and constraints.
Design end-to-end solutions across the post-training stack including SFT data curation, RLHF/DPO pipelines, custom benchmarks, and LLM-as-judge systems.
Author technical proposals, run workshops and POCs, and serve as ongoing technical advisor during delivery.
Innodata is a global data engineering company focused on enabling responsible AI advancement through data, evaluation frameworks, and human expertise. With a 36+ year legacy, they provide high-quality data solutions to foundation model labs, hyperscalers, and enterprise AI teams.
Architect and maintain production high-traffic LLM serving systems.
Optimize throughput, latency, and cost for leading open-source LLMs.
Debug and optimize major inference engines like SGLang, vLLM, or TensorRT using PyTorch and CUDA.
We are building decentralized and confidential machine learning infrastructure to enable user-owned AI. Our team is focused on highly scalable and efficient infrastructure for open-source AI at a global scale, with a culture that values innovation and performance.
Design and build AI applications powered by LLMs, RAG, semantic search, and AI agents.
Develop intelligent pipelines for document ingestion, knowledge extraction, and retrieval.
Build and optimize production AI services using Python and modern AI frameworks.
Implicit builds a leading AI Knowledge Engine for Maintenance and Support. The company is a small, experienced, and highly technical team tackling challenging real-world problems across defense, manufacturing, and customer support.