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Staff AI/ML Engineer, MyHealthTeam
Swoop.com, Inc. · Remote (United States), United States · Remote · Active · $240,000–$260,000 / year · Rippling ATS
Job facts
| Field | Value |
|---|---|
| Company | Swoop.com, Inc. |
| Title | Staff AI/ML Engineer, MyHealthTeam |
| Normalized title | - |
| Department / team | Communities Engineering |
| Location | United States |
| Work model | Remote / Remote |
| Employment type | Full Time |
| Salary | $240,000–$260,000 / year |
| Status | active |
| ATS provider | Rippling ATS |
| Posted / first seen | 2026-02-19 / 2026-05-29 |
| Changed / last seen | 2026-06-06 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Swoop.com, Inc.. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Rippling ATS. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Department jobs | Active postings in Communities Engineering. | Open |
| Work model jobs | Active Remote postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Swoop.com, Inc. |
| Source | f5202b1b-643e-4eee-9493-24e0138c3b2b |
| ATS provider | Rippling ATS |
Description
company
Join us to redefine the patient experience
MyHealthTeam builds communities for people living with chronic and rare conditions. We reach millions of people each month, and we’re investing deeply in AI to help members find the right support, content, and recommendations — safely, responsibly, and at scale.
We’re looking for a Staff AI/ML Engineer who is product-minded, hands-on, and excited to ship production ML/LLM systems that turn messy, real-world text and behavioral data into reliable experiences for patients.
role
What you get to do every day
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. (Staff scope) Lead architecture and technical direction for applied AI across the organization; mentor engineers; establish best practices and reusable platforms.
Examples of problems you might work on
Personalized recommendations for communities, posts, resources, or next-best actions Safer content understanding: detection of misleading/high-risk health claims, escalation workflows Search and discovery improvements using embeddings, hybrid retrieval, and ranking Summarization and structuring of long threads into navigable insights (with safety constraints) Member intent understanding from behavioral + text signals
Must-have qualifications
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
Nice-to-have qualifications
Experience building RAG and retrieval systems: vector databases, hybrid search, ranking, recommendation, query understanding Experience in healthcare or regulated environments, including privacy-by-design, auditability, and safety reviews (HIPAA/PHI familiarity a plus) Experience with streaming/clickstream data, experimentation platforms, and causal/measurement thinking Ability to prototype end-to-end experiences (e.g., Streamlit, Gradio, lightweight frontends) Experience designing LLM safety systems: red-teaming, adversarial testing, prompt injection mitigation, output filtering, human-in-the-loop review
Some tools we use
Databricks/Spark for distributed processing Redshift and BI tools (Looker/Tableau) for analytics Terraform for infrastructure-as-code; Airflow for orchestration; GitHub Actions for CI/CD AWS (including Bedrock) and a mix of private and open-weight models (including fine-tunes where appropriate) Experimentation tooling (A/B testing) and internal UX analytics tools AI-assisted coding tools (e.g., Cursor, Copilot, Claude/OpenAI tooling)
Working model
The MyHealthTeam Engineering team operates in a remote-first environment. This role is fully remote, with optional in-person collaboration at our San Francisco office.
Why MyHealthTeam @ Swoop
Mission-driven work with massive reach: help millions of people find support and better health outcomes High-ownership culture: small teams, fast shipping, visible impact Strong collaboration: product, data, and domain experts working together A chance to shape applied AI in a real consumer product with real constraints
The Company
Swoop, a market leader in privacy-safe, award-winning omnichannel healthcare marketing, connects patients, healthcare providers (HCPs), and brands at scale across all channels. Our teams leverage the power of AI-driven technology combined with real-world data (RWD), first- and zero-party data, and engagement data, to empower pharmaceutical marketers to make faster, more precise decisions that improve patient outcomes.
At Swoop, our mission is to create a future where technology seamlessly connects patients and HCPs in a privacy-safe way, improving the patient journey and driving better health outcomes. Swoop has experienced significant growth and demonstrated an unwavering commitment to innovation, talent development, and enhancing the patient experience. Our acquisition of MyHealthTeam in January 2025 brought vibrant social communities into our omnichannel suite, further bridging the gap between healthcare brands and patients for more impactful and targeted engagement.
We believe our people are our greatest asset. Swoop fosters a culture of innovation and continuous learning, providing employees with rich opportunities for professional growth. This commitment to our team earned us the "Best Places to Work" recognition from Business Intelligence Group in 2025, based on a survey of over 100 employees. We are driven by a patient-first philosophy and are passionate about leveraging technology to create a healthier future.
If you're a driven professional seeking to make a real difference in healthcare marketing at a fast-growing, innovative company, join Swoop and help us revolutionize how brands connect with patients and HCPs.
Application materials
Submit a resume and answer the following two short questions:
Tell us why MyHealthTeam’s mission matters to you. Give one example of a production ML/LLM system you shipped and how you evaluated it.
Full job record
| Job ID | 590c1232e91fa631e6d4f41c1d7b04d618a40a3d |
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| Provider | rippling |
| Provider Job Key | 77510c97-37ab-4b61-b31f-41a7e40856df |
| Title | Staff AI/ML Engineer, MyHealthTeam |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Remote (United States), United States |
| Department | Communities Engineering |
| Team | — |
| Employment Type | full_time |
| Workplace Type | remote |
| Remote Policy | remote |
| Country | United States |
| Region | — |
| City | — |
| Salary Raw | USD 240000-260000 YEAR |
| Salary Min | 240,000 |
| Salary Max | 260,000 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://ats.rippling.com/swoopishiring/jobs/77510c97-37ab-4b61-b31f-41a7e40856df |
| Apply URL | https://ats.rippling.com/swoopishiring/jobs/77510c97-37ab-4b61-b31f-41a7e40856df |
| First Seen At | 2026-05-29 07:17:33Z |
| Last Seen At | 2026-06-06 08:45:25Z |
| Last Checked At | 2026-06-06 08:45:25Z |
| Last Changed At | 2026-06-06 08:45:25Z |
| Inactive At | — |
| Source Posted At | 2026-02-19 21:06:00Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=rippling/board=swoopishiring/date=2026-06-06/2026-06-06T08-45-24-718Z-36f524539ce1beeb7dbf759aff13886a6659873ef94474c33cfd94f3d1fafd4b.json |
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"role": "<meta><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">What you get to do every day</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Build end-to-end ML/LLM features from problem definition → data → modeling → evaluation → deployment → monitoring.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Develop LLM applications with retrieval and tool use (e.g., RAG, orchestration/workflows, structured extraction) to deliver trustworthy consumer health experiences.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">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.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Create and maintain data pipelines for training, inference, evaluation, and analytics (batch and/or streaming as needed).</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Design evaluation systems that measure quality and safety: offline metrics, golden datasets, human review workflows, and online A/B testing alignment.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Implement production guardrails to reduce harm and misinformation risk (policy constraints, refusal behavior, citations/attribution when appropriate, red-teaming, monitoring, and incident response).</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Set up monitoring for model + system health (latency, cost, drift, regressions, quality metrics).</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">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.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">(Staff scope) Lead architecture and technical direction for applied AI across the organization; mentor engineers; establish best practices and reusable platforms.</span><br><br></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Examples of problems you might work on</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Personalized recommendations for communities, posts, resources, or next-best actions</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Safer content understanding: detection of misleading/high-risk health claims, escalation workflows</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Search and discovery improvements using embeddings, hybrid retrieval, and ranking</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Summarization and structuring of long threads into navigable insights (with safety constraints)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Member intent understanding from behavioral + text signals</span><br><br></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:18pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Must-have qualifications</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">8+ years building and shipping production ML systems (or equivalent experience with demonstrable impact)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Strong Python skills and experience with ML/LLM libraries and tooling (e.g., Hugging Face ecosystem, LangChain/LangGraph, or equivalent)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Proven ability to design production-grade pipelines (training/inference/eval) and operate models in real systems (monitoring, rollbacks, incident handling)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Solid grounding in ML fundamentals (NLP, deep learning, statistical reasoning, evaluation)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Experience with MLOps best practices: versioning, reproducibility, CI/CD, model registry patterns, feature/data management, and infrastructure collaboration</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Experience working with large-scale data using Databricks/Spark or equivalent distributed processing</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Strong product and stakeholder instincts: you can translate ambiguous business needs into measurable ML outcomes</span><br><br></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Nice-to-have qualifications</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Experience building RAG and retrieval systems: vector databases, hybrid search, ranking, recommendation, query understanding</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Experience in healthcare or regulated environments, including privacy-by-design, auditability, and safety reviews (HIPAA/PHI familiarity a plus)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Experience with streaming/clickstream data, experimentation platforms, and causal/measurement thinking</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Ability to prototype end-to-end experiences (e.g., Streamlit, Gradio, lightweight frontends)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Experience designing LLM safety systems: red-teaming, adversarial testing, prompt injection mitigation, output filtering, human-in-the-loop review</span><br><br></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Some tools we use</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Databricks/Spark for distributed processing</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Redshift and BI tools (Looker/Tableau) for analytics</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Terraform for infrastructure-as-code; Airflow for orchestration; GitHub Actions for CI/CD</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">AWS (including Bedrock) and a mix of private and open-weight models (including fine-tunes where appropriate)</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"white-space:pre-wrap;\">Experimentation tooling (A/B testing) and internal UX analytics tools</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">AI-assisted coding tools (e.g., Cursor, Copilot, Claude/OpenAI tooling)</span><br><br></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Working model</strong></b></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"white-space:pre-wrap;\">The MyHealthTeam Engineering team operates in a remote-first environment. This role is fully remote, with optional in-person collaboration at our San Francisco office.</span><br><br></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Why MyHealthTeam @ Swoop</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Mission-driven work with massive reach: help millions of people find support and better health outcomes</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">High-ownership culture: small teams, fast shipping, visible impact</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Strong collaboration: product, data, and domain experts working together</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">A chance to shape applied AI in a real consumer product with real constraints</span></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">The Company</strong></b></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Swoop, a market leader in privacy-safe, award-winning omnichannel healthcare marketing, connects patients, healthcare providers (HCPs), and brands at scale across all channels. Our teams leverage the power of AI-driven technology combined with real-world data (RWD), first- and zero-party data, and engagement data, to empower pharmaceutical marketers to make faster, more precise decisions that improve patient outcomes. </span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\"> </span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">At Swoop, our mission is to create a future where technology seamlessly connects patients and HCPs in a privacy-safe way, improving the patient journey and driving better health outcomes. Swoop has experienced significant growth and demonstrated an unwavering commitment to innovation, talent development, and enhancing the patient experience. Our acquisition of MyHealthTeam in January 2025 brought vibrant social communities into our omnichannel suite, further bridging the gap between healthcare brands and patients for more impactful and targeted engagement. </span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\"> </span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">We believe our people are our greatest asset. Swoop fosters a culture of innovation and continuous learning, providing employees with rich opportunities for professional growth. This commitment to our team earned us the \"Best Places to Work\" recognition from Business Intelligence Group in 2025, based on a survey of over 100 employees. We are driven by a patient-first philosophy and are passionate about leveraging technology to create a healthier future. </span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\"> </span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">If you're a driven professional seeking to make a real difference in healthcare marketing at a fast-growing, innovative company, join Swoop and help us revolutionize how brands connect with patients and HCPs. </span></p><hr><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Application materials</strong></b></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Submit a resume and answer the following two short questions:</span></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Tell us why MyHealthTeam’s mission matters to you.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Give one example of a production ML/LLM system you shipped and how you evaluated it.</span></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p>",
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