Machine Learning Engineer

About Baronit:

At Baronit, we connect brilliant minds to shape the future of technology. As a passionate team of tech experts, we lead with innovation, expertise, and curiosity to help businesses grow and adapt to new opportunities. Our experts blend technical excellence, industry insight, and a strong commitment to delivering exceptional results across sectors such as Automotive, Airline, Fintech, Healthcare, Retail, Telecom, E-commerce, and more.

We are an IT consultancy company based in Gothenburg looking for an experienced Machine Learning Engineer to join our team.

Key Responsibilities:

• Establish MLOps best practices and patterns for scalable ML deployment.
• Design and build reproducible ML pipelines and model-serving infrastructure.
• Manage and automate CI/CD for ML using GitHub Actions or Azure DevOps.
• Operate in cloud-first environments (GCP, Azure, AWS), using tools like Vertex AI, DBT, Airflow, or Kubeflow.
• Implement observability (model monitoring, drift detection) and infrastructure-as-code (Terraform, Helm).
• Collaborate with Data Scientists, Engineers, and Analysts to move models from notebooks to production.
• Ensure ML workflows align with data governance, security, and compliance standards.
• Contribute to LLM-based model serving and fine-tuning pipelines where applicable.

Ideal candidate profile:

• Academic degree in Computer Science, Engineering, or a related field.
• 7+ years of experience in Software Development/DevOps or related field.
• 4+ years of experience in ML engineering or MLOps in production settings.
• Proficient in Python (OOP, testing, clean code, package management).
• Experienced in cloud platforms - GCP, Azure, AWS.
• Experienced with AWS services for ML deployment and infrastructure management, including SageMaker, CloudWatch, and IAM.
• Experience developing RESTful APIs using FastAPI for model serving and inference endpoints, including integration with CI/CD and auth middleware.
• Hands-on with CI/CD pipelines, Containerization (Docker, Kubernetes), Infrastructure as Code (Terraform, ArgoCD, etc.), MLFlow, DBT, and Airflow.
• Experience in monitoring/observability strategies for production ML systems, including latency tracking, drift detection, and model version health using Prometheus, Grafana, or Vertex AI Model Monitoring.
• Strong skills in SQL, data modeling, and scalable data pipelines.
• Able to work in agile, cross-functional teams with clear communication and ownership mindset.
• Strong analytical problem-solving skills and love for clean, maintainable systems.
• Curious, experimental, and fast learner with excellent communication skills in English.
• Experience with large language models and LLMOps pipelines is a plus.
• Working knowledge aligned with GCP/AWS ML certification standards (Vertex AI, IAM, Dataflow) is a plus.

In addition to exciting projects, we also offer:

• Flexible salary model – choose between a fixed salary or a revenue-based model where you receive X% of your client rate, with full transparency
• Technical forums for continuous learning and knowledge sharing
• Social activities to stay connected and engaged
• Annual offsite conference for team bonding and inspiration
• And above all – a great team spirit and a focus on enjoying the journey together