We are looking for a machine learning engineer (hybrid of data-oriented developer and machine learning enthusiast) with approximately 0.5-3 years of real-life data experience with building and deploying data science (machine learning / predictive models in R / Python / Spark) to production.
The path from the model on a local desktop to the production ready (self learning, fast, clean) solution is often complicated. The role is about being the glue and link between data scientists and data engineers on the team to work towards a production-ready version of machine learning models. Working with solutions coming out of pilots/PoC/agile development and helping turn them into production-level data pipelines.
Who are we?
We are a machine learning and cloud data engineering boutique - we help clients from different industries (finance, retail, e-commerce, HR, etc.) use advanced data analytics (predictive modelling, machine learning, NLP, etc.) to improve their processes such as:
social network influencer recommendations
predictive cross-sell campaign targeting
display ad micro-targeting
finding the most relevant candidate for the job with NLP, image detection and recognition, etc...
A group of twenty data scientists and data engineers who were bored by large and slow projects in corporations or were lonely in start-ups and set off on another route. We do not have our own product, but we work on a project basis and try to help our clients find the best solutions.
We work in agile / prototype mode and build on modern data and BI technologies, especially in the open-source and cloud world:
Data Preparation / ETL - especially Spark (Databricks), Python, SQL
Machine learning - Spark (Databricks), Python, R
Visualization - Qlik Sense, Tableau, PowerBI
Infrastructure - Azure, AWS, GCP
What would you do?
Working on individual client projects typically in tandem with senior data scientist / architect who gives the project direction and a data scientist and data engineer – in our data strike team.
As part of such a project, you would be responsible for implementing / scaling / refactoring an advanced analytics/machine learning/artificial intelligence, which in practice involves:
Implementing machine learning algorithms / predictive models (trees, regression, xgboost, clustering, recommendation, text mining / NLP, neural networks, etc.) in Python / R / Spark
Data / feature engineering using SQL, Python / R, Spark
DevOps and Cloud Infrastructure - Azure / AWS / GCP
Enthusiasm for exploring and experimenting with new data technologies (streaming, distributed systems, unstructured data)
It's not about how many of these things you already know now, but that you are interested and want to learn them all.
You will like the job when:
You like working in a smaller cross-functional team on something that has a clear business purpose and use
You do not want to explore just one area of data analysis but you are interested in getting to know more clients / industries / projects and technologies
You want to work for a smaller flexible company (a combination of a remote and an office, a flat structure, etc.) and to be part of a team of people like you, so you can help and enrich each other
Write to firstname.lastname@example.org to get to know each other and discuss it in more detail.