Forward-Deployed Data Scientist, AI Deployment (AI Engineering)

TL;DR

Forward-Deployed Data Scientist (AI Engineering): Collaborating with customer Analytics/BI teams and hirify.global colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration with an accent on shaping hirify.globalAI's product strategy and roadmap through customer-facing insights and technical expertise. Focus on ensuring successful adoption, measurable outcomes, and long-term customer success.

Location: Mexico City

Company

hirify.global is the leading customer engagement platform that empowers brands to Be Absolutely Engaging.

What you will do

• Collaborate with customer Analytics/BI teams and hirify.global colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration.
• Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components.
• Refine and advance reinforcement learning (self-learning) algorithms working closely with the RL pipeline development team.
• Contribute to shaping hirify.globalAI's product strategy and roadmap through customer-facing insights and technical expertise.
• Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success.

Requirements

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required; Master’s or PhD in a relevant technical discipline preferred.
• Experience: 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments. Experience in customer-facing or consulting roles is strongly preferred.
• Strong technical expertise: Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost). Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment.
• Engineering best practices: You write well-structured, modular, documented code; follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews); and can build scalable, maintainable solutions.
• Customer collaborator: Comfortable working directly with clients and cross-functional teams, aligning stakeholders, and translating technical concepts into clear business value.
• Clear communicator: Able to explain complex technical ideas persuasively to both technical and non-technical audiences.

Nice to have

• Experience with DevOps tools (Airflow, Kubernetes, Terraform, GCP), data integration/ETL and pipeline optimization, or reinforcement learning algorithms

Culture & Benefits

• Competitive compensation that may include equity.
• Flexible paid time off.
• Comprehensive benefit plans covering medical, dental, vision, life, and disability.
• Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend.
• Collaborative, transparent, and fun culture recognized as a Great Place to Work®.
• Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching.