Machine Learning Engineer Search
1 maand geleden
We help our customers to decide on their purchase and complete their order. Given the amount of data - it's like in a candy shop: figuring out the best treat for our customers is challenging.
How do you make our customers happy?
We are Help Me Find: the teams that are responsible for the search journey of our consumers on web and app. By showing relevant products, based on the user’s input, we enable both consumers to find what they are looking for and create a possibility for our partners to show their goods.
What do you do as Machine Learning Engineer
We are looking for a machine learning engineer for a team that is focused on improving the relevancy of our search results.
The team consists of both data scientists and software engineers. We have developed various data science models which have been tested and have proven to improve our search quality. Now we want to bring these models to production. And that is where you might come in.
We are looking for somebody who has experience with MLOps and knows what it means to bring a machine learning model to production at scale. This not only includes helping the team optimize these models, making them production ready and smoothening the ride towards deployment in a production setting. It also means ensuring that the model can serve its results quickly and efficiently. As such, we prefer somebody with a strong engineering background, but who is also familiar with the challenges of (big) data (science). Knowledge of search systems and algorithms are a big plus.
What we can offer:
- A cross functional team with both experienced data scientists and software engineers.
- An opportunity to Increase your knowledge about data science models and principles.
- Work on a key functionality of bol.com (search).
- A lot of data to play with (search journey information & product information).
The biggest challenge
With millions of active customers and a catalog of over 40 million products, our search needs to be able to properly handle hundreds of wildly varying requests every second.
We must ensure our systems can balance cached solutions with real-time updates, understanding the tradeoff between optimal accuracy and speed. It’s an ongoing challenge as our landscape evolves, new business ideas emerge, while we monitor our cloud costs.
The challenges that you might work on:
- How can we learn from past interactions of users to re-order our search results (machine-learning ranking and personalization)?
- How can we find relevant products on semantic understanding of the customer’s query and context (embeddings)?
- How can we incorporate LLM’s into our search journey and what does this require from an MLOps perspective?
- How can we improve our feedback loop so that our algorithms can adjust in real-time?
- How do we best make use of concepts like entity recognition to best understand our customers intent?
- How can we test and evaluate our Search set-up in an offline fashion, so we can experiment and learn quickly how to improve?
- How do we incorporate a complex machine learning model into a low-latency + high traffic service?
Tech Skills/experience
- Python, PyTorch or Tensorflow.
- NLP and other algorithms relevant to search (such as ranking algorithms).
- GCP Tech used: Vertex AI , Airflow, Dataflow, Pub/Sub, BigQuery, Memorystore & Kubernetes or similar technologies.
- Java & Kotlin (other backend systems in the same scope).
- Elasticsearch and/or vector databases. 3 reasons why this is (not) for you
Pros
- Yes, You are eager to make a difference and work on high impact solutions that will be seen by all our consumers.
- Yes, You like being part of one of the critical consumer journeys of bol.
- Yes, You are not afraid to tackle the challenges that come with high volume, high traffic services.
Cons
- No, You have no interest in search.
- No, Technically challenging work is not your cup of tea.
- No, You don’t like staying up to date with the latest developments around MLOps and AI.
This is where you’ll work
You will work in the Product Help Me Find, part of the Shop Core domain. A number of strategic company objectives for 2024 have impact on the Bol search journey, because of that, we are increasing the number of engineers in the HMF product.
We are splitting one of the teams, to create two separate teams with more focus.
For both teams we are looking for engineers. This vacancy is for the team focusing on increasing the relevancy of our search results. The team will consist of 3 data scientists, 3 engineers, a data analyst and a product manager.
The new team works closely together with the other new team, which focuses on performance of our complete search engine solution (where we are also looking for new backend engineers).
We are proud of testing (almost) all changes with A/B tests or other experiments, to ensure a fast feedback loop between the things we build and what people are actually using.
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