Senior Machine Learning Engineer - Sweden πΈπͺ
Modulai is hiring a Senior Machine Learning Engineer - Sweden πΈπͺ in Stockholm, Sweden. Level rates it ; you can apply on Modulai.
Level's read on this job
- On Level's scale, this machine learning engineer role is Builds AI ββββ: the job is building AI systems.
- Tools and skills the posting cites include scikit-learn and AI evaluation.
- Level classifies it as a senior role.
- Level lists 4 other open roles at Modulai.
AI in this role
SENIOR MACHINE LEARNING ENGINEER (SMLE) - Sweden
As a member of Modulai you will be working with a broad range of problems with one common denominator β ML will be the key ingredient. As a SMLE you will be responsible for team success and advisory to both teams and clients.
In this role, you will be responsible for engaging clients and teams from the initial idea phase through to execution. We are looking for someone with a proven track record of successfully developing end-to-end ML products and leading teams in both commercial and delivery settings. It's important that you have a passion for ML and strong opinions on how to succeed in applied ML. At our company, being a lead is not just a formal title; it's a responsibility to help others achieve even greater success.
You will have to analyze the problem at hand, devise a solution strategy, and execute it. This typically entails gaining an in-depth understanding of the challenge, understanding the available data, and then re-formulating it as an ML problem. It requires openness, creativity, and an eagerness to learn new methodologies and explore new terrains.
We approach these problems as a team where great leaders are essential, meaning that you will have to be able to clearly explain your reasoning and code to engage the team as well as clients, investors, and others.
Responsibilities
Helping the team to succeed as a technical mentor
Challenge and inspire the team in state-of-the-art applied ML
Analyzing and planning problems, solutions, and delivery
Preprocessing, feature engineering, and dataset creation
ML model development
Validation of results
Data pipelining and infrastructure development
Our Stack
Python β standard open-source libraries
Scikit-learn and various specialized Python and R ML libraries
Cloud platforms such as GCP, AWS, Azure
Relational database management systems
Distributed processing such as Apache Spark
Background & Skills
MSc or Ph.D. in a quantitative field
5 years of experience in leading end-to-end ML projects
Experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Experience with software development in one or more programming languages, and with data structures/algorithms.
Excellent communicator (IRL, blog, events, etc)
Excellent understanding of a broad set of ML algorithms and frameworks
A passion for lean, clean, and maintainable code
The desire to grow and to share insights with others
Helpful knowledge & Experience
Leadership in fast-growing organisations
Product experience from idea to MVP and monetization.
Deep learning frameworks and theory
Data pipelining and infrastructure
DevOps experience, CI/CD, Kubernetes
2 years of experience with state-of-the-art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts
NOTE:
To Apply we require a work VISA for Sweden. Currently, we do not offer sponsorships.
Due to the summer holiday period, applications will be reviewed starting 27th of July.
About Team Modulai
At Modulai, we focus 100% on solving problems with machine learning (ML). We work in teams on a project basis, for clients, as part of the core team in startups where we have long-term engagements, and we also build our own ML products.
Learning and teamwork are central to how we work. Everyone in the team is or will soon be a full-stack ML engineer capable of scoping and developing end-to-end ML solutions. You should be able to do end-to-end machine learning products by yourself but never do it because we always work in teams. If there is data, we will do ML on it!
How we rate this
Senior Machine Learning Engineer - Sweden πΈπͺ at Modulai rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ββββ Builds AI80 to 100
- ββββ Works on AI60 to 79
- ββββ Uses AI40 to 59
- ββββ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $197k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- Walk me through how you've used scikit-learn in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Evaluation and scikit-learn. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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