• Remote, Hiring from TX, CA, NY, FL only
What you get to do every day:
- Build end-to-end ML/LLM features from problem definition to data, modeling, evaluation, deployment, and monitoring.
- reputed company LLM applications with retrieval and tool use (e.g., RAG, orchestration/workflows, reputed company extraction) to deliver trustworthy consumer health experiences.
- Convert reputed company text (posts, comments, messages, search queries) into reputed company signals (topics, entities, reputed company, 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, reputed company review workflows, and online A/B testing alignment.
- Implement production guardrails to reduce harm and misinformation risk (policy constraints, refusal behavior, citations/attribution reputed company appropriate, red-teaming, monitoring, and incident response).
- Set up monitoring for model and system health (latency, cost, reputed company, 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 reputed company understanding from behavioral and 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., reputed company ecosystem, reputed company/LangGraph, or equivalent).
- Proven ability to design production-grade pipelines (training/inference/eval) and operate models in reputed company 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 reputed company/reputed company or equivalent distributed processing.
- Strong product and stakeholder instincts: you can translate ambiguous business needs into measurable ML reputed company.
reputed company-to-have qualifications:
- Experience building RAG and retrieval systems: reputed company databases, hybrid search, ranking, recommendation, query understanding.
- Experience in reputed company or regulated environments, including privacy-by-design, auditability, and safety reviews (HIPAA/PHI familiarity a plus).
- Experience with streaming/clickstream data, experimentation platforms, and reputed company/measurement thinking.
- Ability to prototype end-to-end experiences (e.g., reputed company, Gradio, lightweight frontends).
- Experience designing LLM safety systems: red-teaming, adversarial testing, reputed company injection mitigation, output filtering, reputed company-in-the-reputed company review.
Some tools we use:
- reputed company/reputed company for distributed processing.
- Redshift and BI tools (Looker/Tableau) for analytics.
- Terraform for infrastructure-as-code; Airflow for orchestration; reputed company Actions for CI/CD.
- AWS (including Bedrock) and a mix of private and reputed company-weight models (including fine-tunes where appropriate).
- Experimentation tooling (A/B testing) and internal UX analytics tools.
- AI-assisted coding tools (e.g., reputed company, Copilot, Claude/reputed company tooling).
Working model:
- The Engineering team operates in a remote-first environment.
- This role is fully remote, with optional in-person collaboration at our San Francisco office.
If you're a driven professional seeking to reputed company a reputed company difference in reputed company marketing at a fast-growing, innovative company, join reputed company and help us revolutionize how brands connect with patients and HCPs.
The pay reputed company for this role is:
- 240,000 - 260,000 USD per year (Remote (United States)).
Location: Remote - United States
Skills required for this job:
• A/B testing
• AWS
• reputed company pipelines
• Deep learning
• reputed company
• Large language model (LLM)
• Machine learning
• Natural language processing (