Data Engineer – Applied ML
- Level
- Mid
Not stated in the posting: salary, work type, visa.
Open. First seen 2 October 2026.
About the role
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:
- Holds a B.Sc. or M.Sc. in Computer Science, Data Science, Mathematics or another relevant field
- Has 4+ years of hands-on experience as a data engineer, ML engineer or data scientist, with solutions running in production
- Has strong Python skills and writes production-quality code
- Has hands-on experience building LLM-based applications in production (prompt engineering, structured outputs, RAG, embeddings, evaluation)
- Has worked with the modern LLM stack: LLM provider APIs (OpenAI, Anthropic, etc.), LangGraph or LangChain, Hugging Face and vector stores
- Has a solid grasp of text classification and NLP methods, both classical and modern, and knows when to use each
- Has experience processing large-scale data with Spark/PySpark, Databricks or similar, on AWS or another cloud
- Understands evaluation and data quality well: precision/recall trade-offs, building ground truth, error analysis
- Is pragmatic and delivery-focused, comfortable with ambiguity, and communicates clearly with Product and business stakeholders
- Has experience with taxonomies, entity resolution or product/e-commerce data (advantage)
- 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:
Similarweb's standard text
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.
Similarweb's standard text
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/
Similarweb's standard text
We will handle your application and information related to your application in accordance with the Applicant Privacy Policy available here.
What this role asks for
Particular to this role
Hugging Face · NLP · RAG
Rare in Similarweb's other 33 open postings.
Standard for data science / ML roles
LLM · Machine Learning
Common in data science / ML postings at any company.
In most of Similarweb's ads
Python
Named in most of its open postings, whatever the role.
82% of this description is written for the role. The rest is Similarweb's standard text, folded away below.
Read against Similarweb's other open postings on this site.
The team: R&D HIRES STEADILY
This role is one of 26 open in R&D. 7 were posted in the last 30 days and the oldest in February: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (21 of 26), AWS (17 of 26), LLM (11 of 26), Spark (11 of 26), SQL (9 of 26), CI/CD (7 of 26), Databricks (7 of 26)
OTHER ROLES ON THIS TEAM
- Data Analyst posted Oct 15
- Backend Engineer with AI Experience posted Oct 8
- Agent Platform Engineer posted Oct 8
- Senior Backend Engineer - AI platform posted Oct 2
- Product Data Scientist (Customer-facing) posted Sep 29
- Data Scientist Team Manager posted Sep 22
- Lead Data Analyst posted Sep 15
- AI Engineer posted Sep 12
- Senior Full Stack Developer (Backend Oriented) posted Sep 9
- Data Scientist – Ad Intelligence posted Aug 25
- Senior Full Stack Developer posted Aug 24
- Senior Full Stack Developer - B2C posted Aug 14
- ML & Big Data Analyst posted Aug 12
- Principal Tech Lead (Backend oriented) posted Jul 1
- Big Data Engineer posted Jun 1
- Senior Backend Engineer, Platform Foundations posted May 28
- Senior DevOps Engineer posted May 18
- Senior Data Engineer posted May 10
- Product Data Scientist (Client-facing) posted Jan 23
- AI Engineer posted Jan 22
- Senior Data Engineer (Infrastructure) posted Jan 22
- Product Data Scientist (Data Labs) posted May 30
- Big Data Analyst posted May 19
- Data Scientist posted Apr 27
- Analytics Engineer in Data Collection posted Feb 12
From the team and dates on Similarweb's own job board.
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