Senior Machine Learning Engineer, Agentic Context Retrieval and Search (Nova)

Iterable, Inc.; United States; Remoto; USD 150.000 - 200.000; Tempo pieno

Descrizione del lavoro

Iterable, Inc. is seeking a Senior Machine Learning Engineer to lead the development of Nova's retrieval and search stack for enterprise-scale customer engagement.

You will own end-to-end capabilities from research and experimentation to production systems, with autonomy to shape AI directions and deliver grounded, context-aware responses for large-scale deployments. You'll mentor engineers, collaborate with product teams, and contribute to evaluating models with offline benchmarks and live

Competenze

• 5+ years hands-on MLE experience in production at scale, including search, information retrieval, or recommender systems.
• Master's or PhD in CS/ML or a related field.
• Stay current with research and apply it to improve product experiences.
• Deep IR expertise: lexical, dense, and hybrid retrieval; learning-to-rank.
• Production experience with search engines (Elasticsearch/OpenSearch/Vespa) and relevance tuning.
• Experience with RAG, query rewriting, reranking, grounding techniques.
• Experience building agents on retrieval, including multi-hop search or sufficiency checks.
• Strong evaluation: offline benchmarks, AB testing, labeling pipelines.

Mansioni

• Build retrieval across structured data and unstructured content with source-specific signals.
• Develop semantic query understanding for agents: rewriting, decomposition, intent classification.
• Create pipelines to extract entities, embeddings, summaries, and metadata; keep them fresh.
• Build search subagents to decide what to retrieve, run multi-hop searches, and flag failures.
• Measure quality with ranking metrics, LLM judges, and online tests; improve retrieval and harness.
• Mentor engineers and help set Nova's technical direction.

Conoscenze

Machine learning engineering

Production deployment

Information retrieval

Search systems

Recommendation systems

NLP/IR research

Formazione

Masters/PhD in CS/ML

Strumenti

Elasticsearch

OpenSearch

Vespa

RAG pipelines

Descrizione del lavoro

the company is the AI customer engagement platform, built for enterprise scale, loved by teams, and trusted by global brands like Redfin, SeatGeek, Priceline, Calm, and Box. Our platform empowers organizations to activate customer data from any source, design seamless cross-channel experiences, and optimize engagement with Nova Intelligence, the AI layer of our platform, all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on the company to drive growth, deepen customer relationships, and deliver joyful customer experiences.

Our success is powered by extraordinary people who bring our core values to life every day: Be an Owner, Growth Mindset, Run as One, and Transparency. And the market has noticed: G2 recognizes the company as a Leader globally, spanning the Americas, EMEA, APAC, ANZ, and Latin America, with category leadership in Personalization, Marketing Automation, Push Notifications, and Mobile Marketing, and a 4.5/5-star rating from hundreds of users. Gartner named the company a Challenger in the Gartner Magic Quadrant for Multichannel Marketing in both 2024 and 2025. We’ve also earned TrustRadius Top Rated honors in 2024 and 2025, were named a TrustRadius Buyer’s Choice for 2026, and were featured in Snowflake’s Modern Marketing Data Stack 2026.

With a global presence that includes offices in San Francisco, Denver, London, Sydney, and Lisbon, plus remote employees worldwide, we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds. Learn more about our story and mission on our Culture and About Us pages. Let’s shape the future of customer engagement together!

Location: US

About the role

As a high-tech marketing platform, the company works with thousands of large-scale and diverse enterprise customers. the company Nova is our intelligence layer. It helps customer experience teams adapt in real time and improve every interaction.

As a Senior Machine Learning Engineer on Nova, you'll lead context retrieval and search. The goal is agent responses that are grounded in evidence, aware of the customer's context, and based on what a query means rather than its literal words. You will build the retrieval stack and the search subagents that run on top of it.

You will have real autonomy: from research and experimentation through to systems running reliably in production, you'll own this work and help shape the direction of AI at the company.

One of our core values is a growth mindset, and the company is a company where everyone can grow.

What You'll Do

• Build retrieval across structured data (tables, SQL, dashboards, code) and unstructured content (docs, tickets, chat, media), using each source's own signals.
• Build semantic query understanding for agents: query rewriting, decomposition, intent classification, and entity resolution for multi-turn workflows.
• Build pipelines that extract entities, embeddings, summaries, and metadata from customer data, and keep them fresh.
• Build search subagents that decide what to retrieve, run multi-hop searches, check whether results are good enough, and flag when retrieval fails.
• Measure quality with ranking metrics (nDCG, MRR, Recall@K), LLM judges, human labels, and online tests. Track how retrieval affects final responses, and use the results to improve both retrieval and the harness.
• Mentor engineers on the team and help set the technical direction for Nova.

What We’re Looking For

• 5+ years of hands‑on MLE experience putting complex models into production at scale, including search, information retrieval, or recommendation systems.
• Master's or PhD in Computer Science, Machine Learning, AI, or a related field.
• You keep up with the latest research and focus on applying it: shipping reliable changes that measurably improve the product experience for customers.
• Deep IR expertise: lexical (BM25), dense (embeddings, ANN indexes), and hybrid retrieval, plus learning‑to‑rank.
• Production experience with search engines such as Elasticsearch, OpenSearch, or Vespa, including relevance tuning and reranking.
• Hands‑on experience with RAG, query rewriting, reranking, and grounding techniques that reduce hallucination.
• Experience building agents on top of retrieval, such as multi‑hop search or sufficiency checks.
• Strong evaluation practice: offline benchmarks, regression detection, A/B testing, and labeling pipelines.

Bonus points

• Experience with LLM APIs from multiple providers (Anthropic, OpenAI, Google), including tool calling and prompt caching.
• Experience indexing and ranking structured and unstructured data in the same system.

the company is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. the company does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. the company also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, the company will also consider for employment qualified applicants with arrest and conviction records.