Technical Delivery Manager, AI/ML Programs

ABOUT THE ROLE

The Technical Delivery Manager owns end-to-end program management for Innodata's AI/ML engagements, spanning model development, training and fine-tuning, LLM-based solutions, data pipelines, model evaluation and the wider AI/ML workflow. You are accountable for keeping what the client expects and what actually gets delivered tightly aligned at every stage, and for surfacing risk early enough that it can still be solved rather than explained.

This is a client-facing position with real exposure and a technical center of gravity. You are the single point of contact for your accounts, you work with stakeholders from day-to-day contacts up to CXO level, and internally you connect practice heads, engineering, talent acquisition and operations around one delivery plan. This role is not a coordinator role. You are expected to read the guidelines, interrogate the data, challenge the estimates and take a problem apart yourself when the program needs it.

WHAT YOU WILL OWN

• Has owned programs end to end
• Can manage multiple concurrent workstreams
• Has managed scope, timeline, resources, risks and dependencies
• Understands capacity, utilization, productivity and SLA management
• Can manage technical + process + operational teams
• Has experience with governance and executive reporting
• Can manage escalations and corrective actions
• Understands financial/commercial dimensions of delivery
• Has been a primary client-facing SPOC
• Comfortable with enterprise and senior/CXO stakeholders
• Understands quality management in AI/data operations
• Understands QA/QC, calibration, evaluation and quality metrics
• Has meaningful exposure to research or research-driven problem solving

WHAT YOU BRING

• Bachelor's degree in engineering, computer science, data science or a closely related technical / STEM discipline
• 8+ years in technical program, delivery, technology operations, or equivalent leadership
• 2–3+ years managing AI/ML, Data Science, Data Engineering, GenAI, LLM, or related programs
• Strong understanding of the AI/ML lifecycle
• Can discuss model training, fine-tuning, evaluation, data pipelines and MLOps at a working level
• Can understand and challenge technical requirements, workflows, estimates and assumptions
• Comfortable working directly with Data Scientists, ML Engineers and technical SMEs

Strongly Preferred

• Data Science background
• Master’s/PhD or strong technical postgraduate background
• Research publications or substantial research projects
• Experience in reputable AI/ML, technology, consulting or data organizations

Technical Skills

• AI/ML lifecycle. Strong working knowledge of model training and fine-tuning, LLM-based solution delivery, model evaluation and MLOps concepts
• Personal technical working capability. Able to read and challenge guidelines and workflow designs, interrogate delivery and quality data directly, build or modify trackers and utilities, and troubleshoot technical issues alongside engineers rather than delegating every technical decision
• GenAI delivery exposure. Direct exposure to LLM and generative AI delivery, including RAG pipelines, fine-tuning, agentic workflows and evaluation frameworks, is preferred
• Delivery tooling. Practical use of Jira, Asana, MS Project or Confluence, plus reporting and dashboarding tools
• Executive communication. Able to translate technical detail into business impact and present credibly to CXO audiences

HOW YOU WORK

• Orchestrator who stays in the detail. You connect client, engineering, hiring and operations, and remain close enough to the technical work to test assumptions, spot a flawed estimate and take a problem apart personally
• Proactive rather than reactive. You anticipate risks, resourcing gaps and client concerns before they surface as problems
• Credible in both rooms. You are equally at home in a technical review with engineers and a business review with a CXO
• Ownership-driven. You treat client outcomes and program health as personally accountable, end to end
• Comfortable operating on fixed governance cadences, with no tolerance for missed or inaccurate deliverables

DIVERSITY, EQUITY, INCLUSION & BELONGING

At Innodata, Diversity, Equity, Inclusion, and Belonging are at the heart of who we are. With over 35 years of expertise, we foster an inclusive workplace that celebrates the rich diversity of backgrounds, experiences, and perspectives our employees bring — diversity that fuels our innovation in AI and data engineering. We encourage individuals from all walks of life to apply, particularly those who may feel they don't meet every qualification or who hesitate due to their identity. Through inclusive learning initiatives, Employee Resource Groups, and flexible work arrangements, we create a sense of belonging for every team member, whether remote or onsite.

How to Apply

Apply directly through this posting, and our team will be in touch.