
2 - 10 employees
Founded 2025
💼 Consulting
📦 Logistics
📣 Marketing
Consulting • Logistics • Marketing
Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.
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2 - 10 employees
Founded 2025
💼 Consulting
📦 Logistics
📣 Marketing
Consulting • Logistics • Marketing
Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.
• Own end-to-end program delivery across scope, timelines, quality, throughput, contributor performance, and cost. • Design and manage workflows for coding datasets, agentic trajectories, RL environments, benchmarks, and rubric-based evaluations. • Identify operational bottlenecks and improve workflows through better instructions, sequencing, incentives, review systems, and capacity planning. • Define contributor requirements and partner with talent teams to source, assess, onboard, train, and ramp distributed software engineers. • Build team-lead and reviewer structures for programs involving 100–1,000+ contributors. • Own quality-control systems and analyze datasets to identify trends, systematic errors, and root causes. • Act as a primary customer contact for AI labs, communicating progress, risks, quality trends, and recovery plans. • Translate research objectives into practical task specifications and challenge requirements when they may not produce the intended evaluation signal. • Use Python, SQL, or similar tools to automate quality sampling, defect analysis, throughput reporting, and operational reviews. • Convert successful workflows into reusable playbooks, quality controls, evaluation assets, and contributor-management systems. • Share operational learnings and mentor other program leads.
• Proven experience leading complex, multi-stakeholder programs in software engineering, technical program management, consulting, finance, startups, operations, or a similar environment. • Strong analytical and problem-solving skills, including the ability to identify bottlenecks, define meaningful metrics, and improve production performance. • Experience managing distributed teams, contributor networks, marketplaces, or large-scale technical operations. • Strong customer-facing communication skills, including managing expectations, communicating risks, and building long-term client relationships. • Ability to read and review code, understand test suites, and independently assess technical work. • Working knowledge of at least one programming language such as Python, TypeScript, Java, or Go. • Experience using data and operational metrics to monitor quality, throughput, performance, and delivery. • Ability to operate effectively in environments where research requirements and priorities evolve quickly.
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