Full-Time

Senior Applied AI/ML Scientist

Data Science and AI, AI, Data and Intelligence

Updated on 9/4/2026

Sprout Social

Sprout Social

1,001-5,000 employees

Social media management platform with analytics

Compensation Overview

€100k - €135k/yr

Remote in Ireland

Remote

Remote within Ireland; applicants based elsewhere in EMEA cannot be hired at this time.

Bachelor's

Category
Software Engineering (1)
Required Skills
LLM
Datadog
Pinecone
Python
Machine Learning
Observability

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Requirements
  • At least 6 years of experience building and operating production software systems.
  • At least 2 years of hands-on experience shipping large language model-powered features in real-world applications.
  • Strong backend engineering skills, with Python preferred.
  • Experience with large language model APIs such as OpenAI, Anthropic, and open-weight models, and transformer-based techniques.
  • Experience with embedding models and similarity search.
  • Experience with vector databases such as ChromaDB, Pinecone, or Weaviate.
  • Experience with prompt engineering and structured output techniques.
  • Experience with large language model evaluation frameworks and automated testing.
  • Experience with LLMOps practices, including monitoring, versioning, and observability using tools such as Langfuse or Datadog.
  • A track record of owning a system end-to-end in production rather than only contributing to one.
  • Experience making and defending architectural trade-offs involving model choice, build versus buy, and latency versus quality.
  • Experience mentoring engineers or leading technical design reviews.
  • Experience working closely with Product and UX on feature delivery.
Responsibilities
  • Architect and deliver production agentic workflows, including ambient background agents and interactive user-facing tool-using agents.
  • Own the design of large language model-powered content enrichments that feed into customer reporting, alerts, and intelligence briefings.
  • Lead the technical direction for tool-augmented large language model systems, including Model Context Protocol-compatible services, function-calling patterns, and multi-step reasoning workflows.
  • Make architecture-level decisions about when to use retrieval, agents, fine-tuning, smaller models, or classical natural language processing.
  • Define structured prompting standards, output schemas, and reusable patterns for the wider engineering team.
  • Set evaluation practices for large language model systems, including offline benchmarks, online experimentation, regression detection, and human-in-the-loop review.
  • Own guardrails for safety, hallucination reduction, factual grounding, and output consistency.
  • Build observability into every large language model feature, including tracing, cost tracking, latency budgets, quality metrics, and drift monitoring.
  • Make trade-offs between model quality, latency, and cost and remain accountable for them.
  • Evolve embedding and semantic search infrastructure, including chunking strategies, hybrid search, and re-ranking.
  • Improve retrieval relevance as part of a broader agentic architecture.
  • Partner with Product and UX to translate ambiguous AI ideas into shipped customer features.
  • Lead technical design discussions and represent the AI team in architecture decisions.
  • Raise engineering standards through code review, mentorship, and writing, and help less experienced engineers develop as AI practitioners.
  • Evaluate emerging models, frameworks, and techniques and bring appropriate technologies into the stack.
Desired Qualifications
  • Experience with AI orchestration frameworks such as LangChain, LlamaIndex, or LangGraph.
  • Familiarity with Model Context Protocol or tool-calling architectures.
  • Experience building agentic workflows or tool-using systems.
  • Knowledge of semantic search and content retrieval systems.
  • Experience with cloud platforms.
  • A background in media analytics, content intelligence, or large-scale text processing.
  • Experience in startup or high-growth environments.

Sprout Social is a subscription-based platform that helps businesses manage their social media presence with tools for publishing, engaging, listening, and analytics. Users schedule posts, monitor channels, respond to messages, and view dashboards; a premium analytics add-on provides access to over 180 metrics for deeper audience insights and measurement. The product combines publishing, engagement, listening, and analytics in one interface to support social media managers, analysts, and customer care teams. Its goal is to help brands increase awareness, build loyalty, reduce risk, and improve ROI from social media efforts.

Company Size

1,001-5,000

Company Stage

IPO

Headquarters

Chicago, Illinois

Founded

2010

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Simplify Jobs

Simplify's Take

What believers are saying

  • Q2 2026 revenue rose 10.8% to $123.8 million, beating consensus.
  • Non-GAAP operating margin expanded to 12.9%, while free cash flow reached $8.3 million.
  • Management raised 2026 EPS guidance after announcing at least $50 million annualized savings.

What critics are saying

  • Meta, TikTok, and Snap native tools compress Sprout's pricing power through 2027.
  • July 2026 layoffs cut 20% of staff, risking product delays and customer support gaps.
  • If Trellis upgrades stall, Sprout becomes a commoditized dashboard facing eventual platform irrelevance.

What makes Sprout Social unique

  • Sprout Social's Trellis AI turned social signals into workflows, powering June 2026 Snapchat publishing.
  • Enterprise customers above $30,000 ARR grew 20% in Q2 2026, lifting retention.
  • Multi-year contracts formed nearly half of new business, locking in longer revenue visibility.

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Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Retirement Plan

401(k) Company Match

Unlimited Paid Time Off

Wellness Program

Professional Development Budget

Company Equity

Growth & Insights and Company News

Headcount

6 month growth

3%

1 year growth

5%

2 year growth

3%
AdTechEdge
Aug 20th, 2026
Emplifi named Leader in 2026 Social Media Management Data Quadrant.

Emplifi named Leader in 2026 Social Media Management Data Quadrant. Social media management platforms are increasingly becoming broader customer-experience systems as brands attempt to connect social listening, engagement, analytics, commerce and customer care. Emplifi is positioning itself within that shift after being named a Leader in Info-Tech Research Group's 2026 Social Media Management Data Quadrant, based on verified customer feedback. The recognition adds another analyst accolade to Emplifi's recent market momentum, following its inclusion as a Leader in the 2026 Gartner Magic Quadrant for Social Media Management and Listening. More importantly, the two recognitions point to a wider change in enterprise social technology: brands are moving away from isolated publishing tools toward platforms designed to connect customer signals with downstream actions. Emplifi has been named a Leader in Info-Tech Research Group's 2026 Social Media Management Data Quadrant, with the ranking based on verified user feedback collected through Info-Tech's SoftwareReviews platform. The company also received 11 Top Rated Feature awards and 11 Top Rated Capability awards, according to Emplifi, highlighting areas where customers reported strong satisfaction with its social media management platform. Unlike analyst reports based primarily on vendor briefings or product evaluations, Info-Tech's Data Quadrant incorporates feedback from IT and business professionals who use the software. The methodology evaluates both product experience and the broader relationship between customers and software providers. That makes customer feedback particularly relevant in a category where enterprise buyers are increasingly evaluating platforms on more than publishing and scheduling. Social media management has changed substantially over the past decade. What began largely as a workflow for scheduling posts and monitoring mentions has expanded into a broader technology category encompassing social listening, analytics, customer engagement, influencer marketing, commerce and service interactions. Emplifi is attempting to push that evolution further with its Autonomous CX strategy. The company's platform combines social media management, listening, engagement and analytics with AI capabilities designed to help organizations turn customer signals into coordinated actions across marketing, commerce and customer care. That strategy puts Emplifi into competition with a broad group of enterprise MarTech providers, including Sprinklr, Hootsuite, Salesforce, Adobe and Sprout Social. Each takes a somewhat different approach to connecting social media data with customer experience and marketing workflows. The competitive distinction increasingly comes down to how much of that workflow can be unified. For large brands, social data rarely exists in isolation. A customer complaint can begin on Instagram, turn into a customer-service case, influence a marketing response and eventually affect a purchase decision. When those signals remain trapped inside separate systems, teams can lose context and duplicate work. Emplifi's Fuel and Fuel AI offerings are designed around reducing those silos. The company describes the approach as an operating model in which AI helps teams interpret customer signals and recommend or coordinate actions across business functions. That is a notable shift from simply adding generative AI to a social publishing interface. The more consequential opportunity for enterprise MarTech platforms is using AI to connect customer intent, content, engagement and operational decision-making. Instead of asking an AI system to write a social post, marketers increasingly want technology that can identify emerging customer sentiment, determine which issues require attention and help coordinate the appropriate response. That shift also introduces governance challenges. Autonomous or semi-autonomous systems operating across customer-facing functions need clear permissions, data controls and accountability. A social media assistant that generates copy is one thing; an AI system capable of triggering actions across marketing, commerce and customer care carries considerably greater operational risk. Emplifi's positioning around "governed" AI reflects that distinction. The company's CMO, Susan Ganeshan, said the platform is focused on helping organizations make decisions with context and connect customer signals across the lifecycle as AI changes how brands interact with consumers. For enterprise marketing teams, the broader lesson is that social media management is becoming less about channel execution and more about customer intelligence infrastructure. The market is moving in that direction across the major MarTech ecosystem. Salesforce has integrated AI into CRM and customer engagement workflows through its Agentforce platform, while Adobe has expanded AI capabilities across Experience Cloud. Sprinklr has similarly positioned its unified customer experience platform around AI-powered engagement across customer-facing channels. Against that backdrop, analyst recognition can help Emplifi establish credibility with enterprise buyers, but awards alone will not determine platform adoption. The more important question is whether organizations can translate social data into measurable business outcomes without creating another layer of technology complexity. That is where customer feedback becomes significant. The SoftwareReviews recognition indicates that Emplifi's users report positive experiences across specific features and capabilities. For enterprise buyers, however, evaluation will still need to extend into integration, data governance, AI controls, workflow interoperability, analytics depth and total cost of ownership. The recognition nevertheless reinforces the changing role of social platforms inside the enterprise. Social channels are no longer merely destinations for branded content. They are increasingly sources of real-time customer intelligence. The technology challenge is connecting that intelligence to the rest of the customer journey. Emplifi's Autonomous CX strategy is an attempt to make that connection the center of its platform. Market landscape. Enterprise social media management is converging with customer experience management, AI marketing and customer data infrastructure. Traditional platforms focused on publishing, scheduling and basic engagement. Modern enterprise systems increasingly combine those functions with social listening, sentiment analysis, analytics, customer care, commerce and AI-assisted decision-making. The rise of generative and agentic AI is accelerating the transition. Platforms from Salesforce, Adobe, Sprinklr, Hootsuite, Sprout Social and Emplifi are increasingly competing on how effectively they can transform large volumes of customer signals into actionable workflows. The biggest opportunity lies in breaking down organizational silos. Marketing teams may own social publishing, customer service may manage complaints and commerce teams may own purchase journeys, but customers experience those interactions as one relationship with a brand. AI can potentially connect those signals, but only when underlying data, permissions and workflows are integrated. For enterprise buyers, that makes AI governance, interoperability and measurable customer outcomes as important as the number of social networks a platform supports. Top insights. * Emplifi was named a Leader in Info-Tech's 2026 Social Media Management Data Quadrant, based on verified feedback from software users. * The company also received 11 Top Rated Feature and 11 Top Rated Capability awards, reinforcing customer satisfaction across its social management platform. * Emplifi is positioning Autonomous CX as an evolution beyond social publishing toward AI-assisted customer engagement across marketing, commerce and care. * The recognition arrives after Emplifi was also named a Leader in Gartner's 2026 Social Media Management and Listening Magic Quadrant. * Enterprise social platforms are increasingly competing on AI, customer intelligence, workflow integration and governance rather than publishing and scheduling alone.

Yahoo Finance
Aug 15th, 2026
Sprout Social beats Q2 earnings as AI product Trellis boosts customer retention

Sprout Social reported second-quarter results that exceeded Wall Street expectations, with revenue of $123.8 million and adjusted earnings per share of $0.26, beating estimates on both metrics. The social media management platform attributed growth to momentum with enterprise customers, particularly those with annual contracts above $30,000. CEO Ryan Barretto noted that multi-year contracts now represent nearly half of new business. Customers using Trellis, the company's AI offering, showed higher retention rates than others. The company raised its full-year adjusted EPS guidance by 22.2% to $1.13 at the midpoint. Annual recurring revenue reached $506.6 million, though this figure fell short of analyst expectations of $518.5 million. Management indicated that recent workforce reductions were broad-based, aimed at streamlining operations. Early adoption of the paid Trellis Plus tier has begun, with more detailed metrics expected in coming quarters.

Yahoo Finance
Aug 10th, 2026
Sprout Social beats Q2 expectations with $123.8M revenue as AI investment and enterprise upselling drive growth

Sprout Social reported second quarter revenue of $123.8 million, exceeding analyst estimates and marking 10.8% year-on-year growth. The social media management platform's non-GAAP profit of $0.26 per share beat consensus by 62.5%. Chief executive Ryan Barretto attributed the results to momentum with larger enterprise customers and expanded product adoption, particularly in the $30,000-and-above annual contract value segment. Multi-year contracts now represent nearly half of new business. The company raised full-year adjusted earnings guidance by 22.2% to $1.13 per share at the midpoint. Operating margin improved to negative 2.2%, up from negative 11% in the prior year period. Sprout expects efficiency gains from organisational restructuring and continued investment in its AI-powered Trellis offering to support future margin expansion.

Yahoo Finance
Aug 7th, 2026
Sprout Social Q2 revenue up 11% to $123.8M, plans 20% workforce cut to save $50M

Sprout Social reported Q2 revenue of $123.8 million, up 10.8% year over year. The social media management software provider saw its non-GAAP operating margin expand to 12.9%, whilst free cash flow increased roughly 60% to $8.3 million. The company is focusing on larger customers, with subscription revenue from those contributing at least $30,000 in annual recurring revenue growing 20%. Sprout ended the quarter with 3,926 customers in this segment, up 11% year over year. Chief executive Ryan Barretto said the company's AI product, Trellis, is gaining usage and beginning to generate upgrades to its paid tier. Sprout plans a 20% workforce reduction expected to cut annualised non-GAAP costs by at least $50 million, prompting the company to raise its full-year operating income outlook.

Yahoo Finance
Aug 6th, 2026
Sprout Social Q2 2026 revenue grows 11% to $123.8M, non-GAAP operating income beats guidance by $6.1M

Sprout Social reported second quarter 2026 financial results, with revenue reaching $123.8 million, up 11% year-over-year. The AI-powered social intelligence platform saw subscription revenue contribution from customers with $30,000 or more in annual recurring revenue grow 20% year-over-year. The company demonstrated improved profitability, posting non-GAAP operating income of $16.0 million, compared to $10.3 million in the same quarter last year. This exceeded guidance by $6.1 million. GAAP net loss narrowed to $3.1 million from $12.0 million in the prior year period. Non-GAAP net income increased to $15.6 million from $10.7 million. Total remaining performance obligations reached $400.8 million, up 16% year-over-year. Cash and cash equivalents stood at $119.9 million as of 30 June 2026.