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Data Engineer – Applied ML

Similarweb similarweb.com Open
Tel Aviv Mid-level Data Engineering

At a glance

Mid-level Data Engineering role at Similarweb. Tel Aviv.

Pay not stated Data Engineer salary

RoleData Engineering
SeniorityMid-level
LocationTel Aviv
PostedSep 30, 2026
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Build production pipelines that classify, standardize and connect product, brand and category records across sources
  • Create agent-based workflows to automate multi-step data tasks from start to finish
  • Select LLM, embedding, fine-tuned, classical ML or rule-based methods, balancing quality, cost and speed
  • Scale processing across billions of records with Spark, Databricks and cloud infrastructure
  • Set up quality checks using labeled examples, evaluation measures and ongoing monitoring, then run solutions after launch

What you bring

  • At least four years delivering production work in data engineering, ML engineering or data science
  • A relevant bachelor’s or master’s degree, such as in computer science, data science or mathematics
  • Strong Python skills and production experience building applications with LLMs, including retrieval, structured outputs and evaluation
  • Experience with NLP classification, large-scale Spark or Databricks processing, and cloud platforms

Who this fits

This suits a hands-on engineer who can apply NLP and machine learning to messy product data, take systems from prototype into production, and work through trade-offs in accuracy, cost and latency. You’ll partner with Product and R&D teams and collaborate in the Tel Aviv office, with some work-from-home flexibility.

From the employer

Similarweb is the leading digital intelligence platform used by over 3500 global customers. Our wide range of solutions power the digital strategies of companies like Google, eBay, and Adidas.

We help our customers succeed in today’s digital world by giving them access to data-driven insights, competitive benchmarks, strategic analysis, and more.

In 2021, we went public on the New York Stock Exchange, and we haven’t stopped growing since!

We’re looking for a Data Engineer with a strong applied ML focus to join our R&D department!

Why is this role so important at Similarweb?

Our Retail Intelligence products help leading brands and retailers understand how their products, brands and categories perform online. Behind them is data collected from retailers and marketplaces around the world: product pages, brands and categories, each described differently by every site.

Your mission is to turn that data into a single, trusted view: classifying products into a unified taxonomy, normalizing brands and attributes, and matching the same entities across sources. And doing it at scale, across a catalog of more than a billion records that keeps growing and changing every day.

This is an applied ML role within data engineering. You’ll build with LLMs, agentic frameworks such as LangGraph, embeddings and classical ML, and ship them as production pipelines. It’s hands-on work, not research for its own sake, but it takes a real understanding of classification and NLP methods to choose the right tool for each problem and prove that it works.

So, what will you be doing all day?

Your daily responsibilities may include:

  • Designing and building LLM-powered and ML-based pipelines that classify, normalize, structure and match product, brand and category data
  • Building agentic workflows (LangGraph or similar) that automate complex data tasks end to end
  • Choosing the right approach for each problem (LLMs, embeddings, fine-tuned models, classical classifiers or rules), balancing accuracy, cost and latency
  • Scaling solutions to run efficiently over billions of records, using Spark, Databricks and our cloud infrastructure
  • Building evaluation frameworks: ground-truth datasets, labeling processes, quality metrics and ongoing monitoring
  • Taking solutions from POC to production, and owning them after launch
  • Working closely with Product to define requirements and shape the roadmap
  • Collaborating with data engineers, data scientists and other R&D teams on infrastructure and best practices

This is the perfect job for someone who:

  1. Holds a B.Sc. or M.Sc. in Computer Science, Data Science, Mathematics or another relevant field
  2. Has 4+ years of hands-on experience as a data engineer, ML engineer or data scientist, with solutions running in production
  3. Has strong Python skills and writes production-quality code
  4. Has hands-on experience building LLM-based applications in production (prompt engineering, structured outputs, RAG, embeddings, evaluation)
  5. Has worked with the modern LLM stack: LLM provider APIs (OpenAI, Anthropic, etc.), LangGraph or LangChain, Hugging Face and vector stores
  6. Has a solid grasp of text classification and NLP methods, both classical and modern, and knows when to use each
  7. Has experience processing large-scale data with Spark/PySpark, Databricks or similar, on AWS or another cloud
  8. Understands evaluation and data quality well: precision/recall trade-offs, building ground truth, error analysis
  9. Is pragmatic and delivery-focused, comfortable with ambiguity, and communicates clearly with Product and business stakeholders
  10. Has experience with taxonomies, entity resolution or product/e-commerce data (advantage)
  11. Has experience with fine-tuning or deploying open-source models (advantage)

At Similarweb, collaborating with our colleagues in-office creates a more connected, unified culture. Our best work is a product of our face-to-face collaboration, with the ability to work partially from home.

Why you’ll love being a Similarwebber:

You’ll actually love the product you work with: Our customers aren’t our only raving fans. When we asked our employees why they chose to come work at Similarweb, 99% of them said “the product.” Imagine how exciting your job is when you get to work with the most powerful digital intelligence platform in the world.

You’ll find a home for your big ideas: We encourage an open dialogue and empower employees to bring their ideas to the table. You’ll find the resources you need to take initiative and create meaningful change within the organization.

We offer competitive perks & benefits: We take your well-being seriously, and offer competitive compensation packages to all employees. We also put a strong emphasis on community, with regular team outings and happy hours.

You can grow your career in any direction you choose: Interested in becoming a VP or want to transition into a different department? Whether it’s Career Week, personalized coaching, or our ongoing learning solutions, you’ll find all the tools and opportunities you need to develop your career right here.

Diversity isn’t just a buzzword: People want to work in a place where they can be themselves. We strive to create a workplace that is reflective of the communities we serve, where everyone is empowered to bring their full, authentic selves to work. We are committed to inclusivity across race, gender, ethnicity, culture, sexual orientation, age, religion, spirituality, identity and experience. We believe our culture of equality and mutual respect also helps us better understand and serve our customers in a world that is becoming more global, more diverse, and more digital every day.

We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here: https://www.similarweb.com/corp/legal/applicant-privacy-policies/

We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here.

Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Data Engineering

Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.