高级应用AI/ML科学家
Sr. Applied AI/ML Scientist
Description
NewsWhip by Sprout Social 正在寻找一名高级应用 AI/ML 科学家加入其 AI、数据与智能业务部门。
为什么加入 NewsWhip by Sprout Social 的数据科学与 AI 团队?
大多数 LLM 应用只是聊天框的包装。我们的不是。
NewsWhip 实时处理全球新闻——每天数百万篇文章、帖子和信号——并将这一数据流转化为预测性智能,供记者、公关负责人和全球品牌在新闻发生前做出决策。在这个流程中,有趣的问题无处不在:持续监控和丰富内容的环境代理,必须在不断变化的语料库中快速且准确的检索系统,针对幻觉可能带来现实后果的领域的评估框架,以及 LLM 生成的见解需要经得起专业分析师审查的报告流程。
你将在产品、数据和工程的交叉点工作,拥有自主进行架构决策的权力,并得到一家认真对待 AI 质量的公司的支持。如果你希望构建不仅仅是回答问题的 LLM 系统——而是能够在最苛刻的内容领域中推理、检索、丰富并采取行动的系统——这就是你的机会。
你将负责
构建并交付 LLM 驱动的功能
- 设计并交付生产级代理工作流——包括环境型(后台代理,持续丰富、监控、总结并呈现 NewsWhip 数据中的洞察)和交互型(面向用户工具使用的代理,在实时响应记者和公关分析师查询中发挥作用)。
- 负责 LLM 驱动的内容增强设计,直接用于客户报告、警报和情报简报——将原始新闻信号转化为结构化、可决策的输出。
- 主导工具增强型 LLM 系统的技术方向,包括 MCP 兼容服务、函数调用模式和多步骤推理工作流。
- 在何时使用检索、何时使用代理、何时进行微调,以及何时使用小型模型或传统 NLP 方法方面做出架构级别的决策。
- 制定结构化提示标准、输出模式和可重用模式,供更广泛的工程团队在此基础上构建。
推动质量、评估与可观测性
- 设定 NewsWhip 评估 LLM 系统的标准——离线基准测试、在线实验、回归检测和人工审核
查看英文原文
Description
NewsWhip by Sprout Social is looking for a Senior Applied AI/ML Scientist to join its AI, Data and Intelligence Business Unit.
Why join NewsWhip by Sprout Social’s Data Science and AI team?
Most LLM applications are wrappers around a chat box. Ours aren't.
NewsWhip processes the world's news in real time - millions of articles, posts, and signals every day - and turns that firehose into predictive intelligence that journalists, PR leaders, and global brands rely on to make decisions before the news breaks. The interesting problems live everywhere in that pipeline: ambient agents that monitor and enrich content as it flows in, retrieval systems that have to be fast and correct on a corpus that changes by the minute, evaluation frameworks for a domain where hallucination has real-world consequences, and reporting workflows where LLM-generated insights need to stand up to scrutiny by professional analysts.
You'll work at the intersection of product, data, and engineering with the autonomy to make architectural decisions and the support of a company that takes AI quality seriously. If you want to build LLM systems that do more than answer questions - systems that reason, retrieve, enrich, and act across one of the most demanding content domains there is — this is the role.
What you'll do
Build and Ship LLM-Powered Features
- Architect and deliver production agentic workflows — both ambient (background agents that enrich, monitor, summarise, and surface insights across NewsWhip's data continuously) and interactive (user-facing tool-using agents that respond to journalist and PR analyst queries in real time).
- Own the design of LLM-powered content enrichments that feed directly into customer reporting, alerts, and intelligence briefings — turning raw news signals into structured, decision-ready outputs.
- Lead the technical direction for tool-augmented LLM systems, including MCP-compatible services, function-calling patterns, and multi-step reasoning workflows.
- Make architecture-level decisions about when to use retrieval, when to use agents, when to fine-tune, and when a smaller model or classical NLP approach is the right answer.
- Define structured prompting standards, output schemas, and reusable patterns that the wider engineering team can build on.
Drive Quality, Evaluation, and Observability
- Set the bar for how NewsWhip evaluates LLM systems — offline benchmarks, online experimentation, regression detection, and human-in-the-loop review.
- Own guardrails for safety, hallucination reduction, factual grounding, and output consistency in a domain (news and media intelligence) where accuracy is non-negotiable.
- Build observability into every LLM feature: tracing, cost tracking, latency budgets, quality metrics, and drift monitoring.
- Make pragmatic trade-offs between model quality, latency, and cost — and be accountable for them.
Retrieval, Embeddings, and Semantic Infrastructure
- Evolve the embedding and semantic search infrastructure that underpins NewsWhip's intelligence layer, including chunking strategies, hybrid search, and re-ranking.
- Improve retrieval relevance as one component of a broader agentic architecture — not as an end in itself.
Lead Technically and Influence Cross-Functionally
- Partner with Product, and UX to translate ambiguous AI ideas into shipped features customers actually rely on.
- Lead technical design discussions and represent the AI team in architecture decisions.
- Raise the bar through code review, mentorship, and writing — help less experienced engineers grow into strong AI practitioners.
- Stay close to the frontier: evaluate emerging models, frameworks, and techniques and bring the right ones into the stack.
What you’ll bring
We’re looking for an experienced and highly technical Senior Applied AI/ML Scientist who embraces challenges, practices a growth mindset, and is eager to collaborate with a variety of stakeholders to provide data-driven solutions to business leaders and to NewsWhip’s by Sprout Social customers.
Minimum Qualifications
- 6+ years of experience building and operating production software systems.
- 2+ years hands-on experience shipping LLM-powered features in real-world applications.
- Strong backend engineering skills (Python preferred).
- Experience with several of the following:
- Large Language Model APIs (OpenAI, Anthropic, open-weight models, etc.) and transformer-based techniques
- Embedding models and similarity search
- Vector databases (ChromaDB, Pinecone, Weaviate, etc.)
- Prompt engineering and structured output techniques
- LLM evaluation frameworks and automated testing
- LLMOps practices (monitoring, versioning, observability using Langfuse, Datadog, etc.)
- Track record of owning a system end-to-end in production, not just contributing to one.
- Experience making and defending architectural trade-offs (model choice, build vs. buy, latency vs. quality).
- Experience mentoring engineers or leading technical design reviews.
- Experience working closely with Product and UX on feature delivery.
Preferred Qualifications
- Bachelor’s in Data Science, Computer Science, Machine Learning, AI, or a related discipline.
- Experience with AI orchestration frameworks (LangChain, LlamaIndex, LangGraph, etc.).
- Familiarity with Model Context Protocol (MCP) or tool-calling architectures.
- Experience building agentic workflows or tool-using systems.
- Knowledge of semantic search and content retrieval systems.
- Experience with cloud platforms.
- Background in media analytics, content intelligence, or large-scale text processing.
- Experience in startup or high-growth environments.
How you’ll grow
Within 1 month, you’ll plant your roots, including:
- Complete onboarding and gain a deep understanding of NewsWhip’s product, data model, and AI roadmap.
- Meet and learn from assigned onboarding resources.
- Set clear expectations and goals with your manager.
- Familiarize yourself with our existing LLM infrastructure, evaluation practices, and vector systems.
- Ship your first meaningful improvement or feature iteration to production.
- Become familiar with our existing features, available data, and best practices.
Within 3 months, you’ll start hitting your stride by:
- Take ownership of a core LLM-powered feature or subsystem.
- Implement measurable improvements to prompt quality, retrieval relevance, or model performance.
- Contribute to improving our AI evaluation and testing strategy.
- Lead at least one technical design discussion related to AI architecture.
Within 6 months, you’ll be making a clear impact through:
- Drive the end-to-end delivery of a significant AI feature from concept to production launch.
- Establish reusable patterns or tooling that improve LLM development velocity and reliability.
- Demonstrate measurable impact on quality metrics (e.g., reduced hallucination rates, improved relevance, latency, or cost efficiency).
Within 12 months, you’ll make this role your own by:
- Be recognized as a go-to expert for LLM systems and applied AI best practices within the team.
- Help shape the longer-term AI architecture and technical roadmap.
- Mentor other engineers on prompt design, evaluation, and AI system reliability.
- Surprise us - propose and deliver AI innovations that meaningfully change how customers use NewsWhip.
Of course what is outlined above is the ideal timeline, but things may shift based on business needs and other projects and tasks could be added at the discretion of your manager.
Our Benefits Program
We’re proud to regularly be recognized for our team, product and culture. Our benefits program includes:
- Comprehensive Private Health & Dental: 100% premium coverage for you and your eligible dependents through VHI (Health) and DeCare (Dental).
- Pension Scheme: We match your pension contributions 1-to-1 up to 6% of your salary.
- Life & Disability Insurance: 100% paid-for life cover and disability insurance for your peace of mind.
- Generous Paid Time Off: 25 days of leave, plus all public holidays and additional company-wide Rest & Recharge days.
- Paid Parental Leave: We support all growing families with 26 weeks of full pay for birthing parents and 16 weeks of full pay for non-birthing parents.
- Family & Care Support: Access to subsidized child/eldercare through .
- Premium Mental Health Support: Full access to Modern Health for you and your dependents, including free coaching, therapy sessions, and digital wellness resources.
- Lifestyle Spending Account (LSA): An annual $700 USD fund to spend on your physical, mental, and financial well-being.
- Work From Home Support: A one-time $550 USD stipend to set up your home office, plus a monthly $50 USD stipend for internet.
- Dublin Office Perks: A €18 daily lunch stipend (via Deliveroo) when you work from our Dublin office.
- Commuter Savings: Access to the Tax Saver Commuter/Cycle to Work scheme for tax savings.
- Charitable Giving: A company match for your donations to eligible organizations.
*This list is for informational purposes only. Benefit offerings are discretionary and subject to change and do not constitute a contract or guarantee of benefits.
Whenever possible, we want to provide team members the flexibility to work in the location that makes the most sense for them. If you prefer an office setting, this role may be based in our Dublin location. If you prefer to work remotely from another location within Ireland, we will accommodate you as best as possible.
If you are based in another location within EMEA, we aren’t able to hire in your location at this time.
Sprout Social Inc. and its subsidiaries process personal data submitted through your application to assess your qualifications for employment and to inform our hiring decision and, where applicable, for required governmental reporting. For more information, please review Sprout's Global Applicant Privacy Notice.
Originally posted on Himalayas