Head Of Ai Enablement

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Job Responsibilities:
The Head of AI Enablement is senior member of the technology organization, pivotal to the growth and success of Welocalize's AI/MT service offerings, focusing on all aspects of the AL/ML operational lifecycle. Key responsibilities include designing and executing AI enablement strategy and product positioning, pre-sales engagement for new opportunities, regular consultation on optimal MT platforms with an informed understanding of the market landscape. This role will lead the AI enablement team that will be responsible for service delivery and AI enablement product support, which will include preparation, building, deploying, and maintaining machine generated translation engines. This role must be accustomed to working within traditional localization workflows, TMSs, and quality processes though eager to transition to workflows that implement generative AI solutions using NLP/LLM focused languages.
Tasks and Responsibilities of the Head of AI enablement:

• Strategic Leadership: Design and execute AI enablement strategy in close collaboration with Welocalize leadership. This will include but not be limited to incorporating market research, customer research and technology evaluation
• Team Leadership: This leaders will be responsible for building and fostering and industry leading team to design and execute product and service delivery. This organization will be at the forefront of developing technologies to support AI enablement and evolving product and service strategy.

a. Engage on optimization of MT based upon currently-available commercial MT, and other models housed within one of the TMSs (phrase, XTM)
b. Engage on (vs lead) the technical development of new MT solutions.
c. Lead customer engagement and strategy for pilots and new initiatives for AI solutions

• Customer-Facing SME for Operational AI/ML Solutions: Actively participate with new sales opportunities particularly as it relates to AI/MT Offerings, with a constant pulse on the competitive landscape to understand how to best position Welocalize services.
• Maximize Inclusion of AI/ML in Workflows: Spread AI-first mentality with Welocalize. Proactively identify opportunities for and drive adoption of machine generated content (LLM or NMT), as well as other AI/ML that is operationalized post R&D.
• Manages Stakeholder Relationships: Effectively manages relationships with key stakeholders, including executive leadership, external partners, and clients, ensuring clear communication and alignment of objectives.
• Coordinates Across Departments: Regularly coordinates with various departments, including Solutions, AI/ML Engineering, and business teams, to ensure that machine translation solutions effectively meet business needs and customer expectations.
• Evaluates and Measures Impact: Critically evaluates the financial impact of machine translation on business outcomes, using metrics to assess success and identify areas for improvement.
• Facilitates Knowledge Sharing and Collaboration: Encourages knowledge sharing and collaboration within and across teams, organizing workshops, seminars, and collaborative sessions to foster a culture of open communication and innovation.

Success Indicators for a Head of AI Enablement:

• Strategic Impact: Success is demonstrated through the strategic impact of AI enablement products and services, as demonstrated by increased customer utilization and acquisition.
• Positive Stakeholder Engagement: Strong engagement with stakeholders at all levels, ensuring alignment of machine learning strategies with business objectives and stakeholder expectations.
• Operational Efficiency: Identification and reduction of manual processes as it relates to NMT or LLM training.

REQUIREMENTS
Education

• BSc in Computer Science, Data Science, Engineering, or relevant experience

Experience

• 10+ years of engineering experience, with a focus on product development. AI/ML engineering experience a plus.
• Localization and project management experience preferred.

Skills & Knowledge

• Proficiency in Programming Languages Commonly Used in NLP: Proficiency in programming languages commonly used in NLP, such as Python, and libraries/frameworks like TensorFlow, PyTorch, or spaCy and strong understanding of software engineering principles and best practices.
• Knowledgeable of LLMs and Capabilities: Experience working with Large Language Models, such as GPT-4, Llama 2, and other commercial or open-source models in production environment. Expertise in LLM strengths as it relates to machine generated translation abilities a plus.
• Strategic Thinking in AI Implementation: Ability to strategically plan and implement AI solutions that align with business objectives and drive growth of Machine Translation service offering.
• Strong Communication Skills: Ability to effectively articulate technical concepts to both technical and non-technical audiences. Experience with data visualization tools and techniques to effectively communicate and present findings a plus.
• High-Level Project Management: Advanced project management skills, capable of leading large-scale projects and ensuring successful outcomes.
• Effective Stakeholder Management: Experience engaging with stakeholders and translating complex technical details into business insights.
• Continuous Learning and Innovation: A commitment to continuous learning, staying aHead of emerging trends as it relates to machine generated translation & understanding the offerings of companies in our space.

Additional Job Details: