ML Engineer: Build Impactful AI & Data Science Solutions

Deploja-Ab; Malmö kommun; On-site; SEK 700,000 - 1,100,000; Full time

Job summary

Deploja is seeking a consultant with deep Python programming and extensive machine learning experience. The role involves applying ML and data science techniques across client and internal projects, including classification, clustering, feature engineering, anomaly detection, and neural networks.

You will engage with LLMs, prompting and agent-based workflows to design practical, scalable solutions. Strong knowledge of classical ML algorithms (SVM, Random Forest, Naive Bayes, k-NN) and framework

Qualifications

• Must-have: strong Python programming and extensive ML/data science experience.
• Must-have: ML pipeline and feature engineering expertise.
• Must-have: experience with LLMs, prompting and agent-based workflows.
• Must-have: solid knowledge of classical ML algorithms (SVM, RF, NB, k-NN).
• Must-have: experience with ML frameworks PyTorch, TensorFlow, Keras, scikit-learn, NumPy and Pandas.
• Must-have: strong analytical thinking and problem-solving skills.
• Must-have: ability to balance creativity with practical delivery in existing systems.
• Must-have: excellent written and verbal communication skills.
• Must-have: proactive, ownership-driven mindset in fast-paced environment.
• Must-have: experience with Scala or Java.
• Must-have: knowledge in NLP, information retrieval, data mining.
• Must-have: experience in statistical modeling and building predictive models.

Skills

Python

Machine Learning

Data Science

LLMs

Prompting

Agent workflows

Statistics

NLP

Information Retrieval

Data Mining

Scala or Java

Tools

PyTorch

TensorFlow

Keras

Scikit-learn

NumPy

Pandas

Job description

Deploja is seeking a consultant with deep Python programming and extensive machine learning experience. The role involves applying ML and data science techniques across client and internal projects, including classification, clustering, feature engineering, anomaly detection, and neural networks.

You will engage with LLMs, prompting and agent-based workflows to design practical, scalable solutions. Strong knowledge of classical ML algorithms (SVM, Random Forest, Naive Bayes, k-NN) and framework