Responsibilities

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

Requirements

• 3–10 years of hands-on ML engineering, data science, or growth analytics experience.
• Strong Python skills with practical experience in PyTorch and/or TensorFlow for building and deploying models.
• Proven track record with data-driven growth systems: lead scoring, conversion prediction, user modeling, or campaign optimization.
• Experience integrating with marketing and CRM platforms (e.g. HubSpot, Salesforce) in ML-driven workflows.
• Familiarity with advertising APIs (e.g. Google Ads, Meta Ads) for model-driven campaign optimization.
• Experience with LLMs, recommender systems, and generative AI techniques.
• Strong cross-functional communication skills to bridge technical and growth teams.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field — or equivalent practical experience.