Senior Engineering Manager

Summary

Join Turing as a Delivery Manager and lead the end-to-end execution of LLM training projects, managing cross-functional teams and ensuring high-quality data and model improvements. You will be the senior project owner, responsible for client alignment, throughput, quality, and operational efficiency. This role demands hands-on leadership, team scaling, stakeholder management, and a strong understanding of LLM development. You will manage multiple concurrent LLM training streams across various languages and domains. The ideal candidate possesses a blend of technical fluency and operational leadership, enabling them to lead delivery in AI/LLM training projects without needing to code.

Requirements

• 4–8 years of experience in a Delivery Manager, Program Manager, or similar role within a technical or data-driven environment
• Proven track record in managing end-to-end project lifecycles, scaling teams, and optimizing delivery pipelines
• Strong experience in client-facing roles involving requirements gathering, delivery tracking, and stakeholder alignment
• Experience managing diverse and distributed teams
• Skilled in driving team performance, managing escalation workflows, and balancing speed, quality and cost
• Working knowledge of Python and/or JavaScript to effectively engage with Engineering Managers and assess code-level output quality
• Proficient in using project management and tracking tools (e.g., Airtable, Notion, JIRA, Asana, Google Sheets)
• Exceptional communication and documentation skills - comfortable leading async and live updates across technical and non-technical audiences
• Strong decision-making, prioritization, and conflict-resolution abilities in dynamic, high-stakes environments

Responsibilities

• Own full project lifecycle from kickoff and scoping to delivery and stabilization
• Manage multiple concurrent LLM training streams (Evals, SFT, RLHF, RLEF, etc.,) across languages and domains
• Lead and coordinate distributed remote teams including AI trainers, team leads and engineering managers
• Maintain strong alignment with Engineering Managers, ensuring delivery of technically sound and review-compliant datasets
• Monitor throughput, quality, rework, review coverage and staffing requirements
• Act as the strategic point of contact for clients - gathering requirements, aligning on expectations, and managing feedback loops
• Build and maintain detailed project trackers, dashboards, and delivery health reports
• Proactively flag risks and drive resolution to ensure uninterrupted, high-quality delivery
• Set up scalable processes, SOPs, and review systems to mature project operations
• Own delivery-level quality KPIs across all roles from trainers to engineers
• Ensure clarity, accuracy, and completeness in outputs: code, responses, explanations, and evaluations
• Work closely with team leads to implement quality review loops and resolve systemic quality gaps
• Identify inefficiencies and continuously optimize workflows and operational structure
• Ensure all output meets the highest standards expected by AI researchers and clients

Preferred Qualifications

• Background in Machine Learning or Data Science is a plus
• Familiarity with LLM concepts, training cycles, or evaluation methods (e.g., RLHF, SFT, RAG)
• Hands-on experience with LLM APIs (GPT, Gemini, Claude, etc.) and RAG workflows

Benefits

• Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
• Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
• Competitive compensation
• Flexible working hours
• Full-time remote opportunity