Hiring in AI and machine learning
Machine learning and applied AI pointed at language — machine translation, model adaptation, evaluation, and the data and model products behind them. Global Search RC places the commercial and business-development leadership that turns language-AI capability into revenue: the people who open new markets, sell data and model services, and own the number as the industry's economics shift.
Roles
What roles exist in AI and machine learning?
- Business development directorOpens new markets, partnerships and revenue lines for a language business — new logos, new verticals, channel and alliance relationships, rather than managing an existing book.
- Enterprise account executiveCarries a quota selling language services or language technology into enterprise accounts — a consultative, long-cycle, multi-stakeholder sale that rewards genuine domain credibility.
- Chief revenue officerOwns all revenue functions across a language business — sales, marketing and customer success — and the commercial strategy for a market being reshaped by AI.
Also hired here
- Chief revenue officer
- Head of partnerships
- Enterprise account executive
- Product marketing lead
- Alliances manager
Supply
What makes AI and machine learning hard to hire for?
The commercial challenge in language AI is that the buyers, the products and the pricing are all new and moving. Selling here needs someone who can build a market that barely existed a year ago and hold a credible conversation with sophisticated technical buyers — origination plus depth, which is a short list.
It is also the part of the industry where a strong commercial hire has the highest leverage and the highest cost of a miss, because a single enterprise or AI-lab relationship can be a large share of revenue.
Cycle
What does the hiring cycle look like?
Long, and heavily dependent on how clearly the commercial mandate is scoped before the search starts. A vague 'go sell our AI' brief is the most common reason these searches fail; a specific market and buyer to open is what strong candidates respond to.
Getting in
How do you move into AI and machine learning?
Usually a strong enterprise seller or business-development leader from an adjacent technology market who brings a network and learns the language-AI domain, or a commercial operator from inside the industry moving up into revenue ownership.
Questions
Hiring in AI and machine learning: common questions
- What kind of commercial leader do we need to sell AI and data services?
- More often a business-development profile than a classic account manager — someone who can create a market rather than work an existing one. The buyers, pricing and use cases are still forming, so the hire has to originate relationships and build the commercial model, not just manage a pipeline that already exists.
- Why do commercial searches in language AI stall so often?
- Usually the brief. If the mandate is written as generic 'AI sales' rather than a specific market, buyer and offer, strong candidates cannot tell what they would actually be selling and self-select out. Scoping the real commercial opportunity before the search starts fixes more failed searches than raising the package does.
How we hire for it
Four practices, one vertical
- Executive searchRetained search for the roles that set direction.
- Talent searchSpecialist individual contributors and middle management.
- Interim expertiseContract and fractional cover for a defined piece of work.
- Growth advisoryDelivery model change, AI adoption, and the org design that follows.
Elsewhere
The other eight verticals
- Translation technologyTMS, CAT and connector platforms. The commercial leadership that takes language technology to market.
- Localization servicesLSPs and in-house localization teams. Commercial, operations and delivery leadership.
- Speech technologyASR, TTS and voice. Commercial and go-to-market leadership for speech products.
- Natural language processingNLP and evaluation. Commercial and pre-sales leadership for language-model products.
- Language data and annotationLanguage data and annotation. Commercial and program leadership for data services.
- Interpretation and RSIRemote and on-demand interpreting. Commercial and operations leadership, healthcare-driven.
- Media localizationSubtitling, dubbing and access services. Commercial and operations leadership.
- Gaming localizationPublisher and studio-side games localization. Commercial and production leadership.
Hiring in AI and machine learning?
A consultation is a 30-minute call about the role, the market and whether the brief is winnable as written.