Senior ML Engineer: Lead Production ML & Cloud Deployments

Datatonic; Göteborgs kommun; Hybrid; SEK 900,000 - 1,300,000; Full time

Benefits offered by this job

Health Perks

Wellness Allowance

WFH Equipment Allowance

Udemy Access

Pension Plan

Job summary

Datatonic in Gothenburg is seeking a Senior Machine Learning Engineer to craft production-grade Python code and lead ML projects for clients. You will build trusted client relationships and translate business needs into scalable ML solutions.

The role combines hands-on engineering with opportunities to guide discussions and shape project delivery, using Google Cloud tools and best practices in ML, data engineering, and MLOps.

Qualifications

• Proficient in Python with production-grade code quality.
• Strong ML and data science fundamentals.
• Experience translating business needs into ML solutions.
• Familiar with CI/CD pipelines and production workloads.
• Excellent communication and client-facing skills.
• Experience with cloud services and deployments.

Responsibilities

• Translating Requirements: Interpret vague requirements and develop models to solve real-world problems.
• Data Science: Conduct ML experiments using programming languages with machine learning libraries.
• Optimisation: Optimise machine learning solutions for performance and scalability.
• Custom Code: Implement tailored machine learning code to meet specific needs.
• Data Engineering: Ensure efficient data flow between databases and backend systems.
• MLOps: Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage.
• ML Architecture Design: Create machine learning architectures using Google Cloud tools and services.
• Engineering Software for Production: Build and deploy production-grade software for ai and data-driven solutions.

Skills

Python

ML & AI

Data Science

CI/CD

Communication

Tools

Flask

SQL

GCP

Job description

Datatonic in Gothenburg is seeking a Senior Machine Learning Engineer to craft production-grade Python code and lead ML projects for clients. You will build trusted client relationships and translate business needs into scalable ML solutions.

The role combines hands-on engineering with opportunities to guide discussions and shape project delivery, using Google Cloud tools and best practices in ML, data engineering, and MLOps.