Staff AI/ML Engineer

🕒 February 20

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Swoop

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2011

⚕️ Healthcare Insurance

💳 Fintech

💊 Pharmaceuticals

Healthcare Insurance • Fintech • Pharmaceuticals

Swoop is a marketing solutions company aimed at the pharmaceutical and life sciences industries, specializing in direct-to-consumer (DTC) and healthcare provider (HCP) marketing. The company leverages advanced AI technology and data to enhance patient-centric engagement and create meaningful connections between patients, healthcare providers, and brands. By focusing on privacy-compliant omnichannel strategies, Swoop seeks to optimize healthcare marketing performance and improve health outcomes across various platforms, including social media and television.

📋 Description

• Build end-to-end ML/LLM features from problem definition → data → modeling → evaluation → deployment → monitoring. • Develop LLM applications with retrieval and tool use (e.g., RAG, orchestration/workflows, structured extraction) to deliver trustworthy consumer health experiences. • Convert unstructured text (posts, comments, messages, search queries) into structured signals (topics, entities, intent, sentiment, safety flags) using a mix of classical NLP and modern LLMs. • Create and maintain data pipelines for training, inference, evaluation, and analytics (batch and/or streaming as needed). • Design evaluation systems that measure quality and safety: offline metrics, golden datasets, human review workflows, and online A/B testing alignment. • Implement production guardrails to reduce harm and misinformation risk (policy constraints, refusal behavior, citations/attribution when appropriate, red-teaming, monitoring, and incident response). • Set up monitoring for model + system health (latency, cost, drift, regressions, quality metrics). • Partner closely with the Product, Engineering, and Data teams and clinical/subject-matter experts to validate outputs and define what “correct” means for sensitive, health-adjacent use cases. • Lead architecture and technical direction for applied AI across the organization; mentor engineers; establish best practices and reusable platforms.

🎯 Requirements

• 8+ years building and shipping production ML systems (or equivalent experience with demonstrable impact) • Strong Python skills and experience with ML/LLM libraries and tooling (e.g., Hugging Face ecosystem, LangChain/LangGraph, or equivalent) • Proven ability to design production-grade pipelines (training/inference/eval) and operate models in real systems (monitoring, rollbacks, incident handling) • Solid grounding in ML fundamentals (NLP, deep learning, statistical reasoning, evaluation) • Experience with MLOps best practices: versioning, reproducibility, CI/CD, model registry patterns, feature/data management, and infrastructure collaboration • Experience working with large-scale data using Databricks/Spark or equivalent distributed processing • Strong product and stakeholder instincts: you can translate ambiguous business needs into measurable ML outcomes.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Professional development opportunities