Responsibilities

• Build ML models to optimize lead scoring, conversion prediction, and campaign performance.
• Automate demand generation workflows covering audience segmentation and personalized outreach.
• Design and maintain data pipelines for behavioral analytics, targeting, and A/B experimentation.
• Partner with marketing and product teams to translate growth goals into measurable ML solutions.
• Experiment with LLMs, recommendation systems, and generative AI for content creation and outreach.
• Establish data-driven frameworks for channel optimization and ROI tracking.

Requirements

• 3–10 years of hands-on ML engineering experience in demand generation, growth marketing, or data-driven marketing domains.
• Strong proficiency in Python, with practical experience using PyTorch and/or TensorFlow to build and deploy models.
• Experience integrating marketing and CRM platforms (e.g. HubSpot, Salesforce) into ML-driven workflows.
• Familiarity with advertising APIs (e.g. Google Ads API, Meta Ads API) for model-driven campaign optimization.
• Proven ability to develop ML solutions for lead scoring, conversion prediction, and performance optimization.
• Hands-on experience with LLMs, recommender systems, and generative AI techniques.
• Strong cross-functional communication skills and a track record of delivering measurable growth impact.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.