Arbetsbeskrivning

About Baronit:

Shaping the Future with Brilliant Minds

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, Fintech, Healthcare, Telecom, E-commerce, and more.

We are an IT consultancy company based in Gothenburg looking for an experienced AI/ML Engineer to join our dynamic team. In this role, you will be responsible for designing, building, and optimizing advanced AI and machine learning solutions, ensuring their seamless deployment in real-world applications. You will work at the intersection of software engineering, machine learning, and AI architecture, with a focus on creating scalable, high-performance systems. The role also requires expertise in MLOps to ensure efficient pipeline integration and model deployment.

Here's what we’re looking for in an ideal candidate:

• Academic degree in Computer Science, Engineering, or a related field.
• 8+ years of experience in related fields.
• Develop and Deploy AI/ML Models: Design, build, and deploy machine learning models and AI systems using frameworks like TensorFlow, PyTorch, and OpenAI. Implement advanced generative AI techniques and other state-of-the-art models, ensuring performance at scale.
• Software Engineering: Apply software engineering principles, including clean coding practices, CI/CD, and containerization for deploying AI/ML systems using languages such as Python, Scala, Java, and C++.
• Data Processing and Pipelines: Build and maintain efficient data pipelines for large-scale datasets, leveraging ETL processes and batch or real-time streaming data. Utilize tools such as Google Cloud Platform, Azure ML, and other cloud platforms for large-scale AI/ML implementations.
• MLOps and DevOps Integration: Lead the implementation of MLOps practices, automating model training, retraining, and deployment workflows using Azure DevOps, CI/CD, and version control tools like Git. Ensure scalability, security, and governance in machine learning pipelines.
• Model Monitoring and Optimization: Monitor models in production environments for drift and degradation. Implement retraining and versioning strategies for continuous improvement.
• Collaboration and Leadership: Work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to translate business requirements into technical solutions.
• Experience with Agile/Scrum methodologies and working in a fast-paced, collaborative environment.
• Strong communication, analytical and problem-solving skills, with a focus on continuous improvement and innovation.
• Fluent in English both written and verbal.

Required Skills:

• Proficiency in Python, Scala, Java, and C++.
• Deep knowledge of TensorFlow, PyTorch, OpenAI, and Transformer models. Experience in building and deploying generative AI models is preferred.
• Strong experience with cloud platforms like Google Cloud Platform, Azure ML, or similar environments.
• Hands-on experience with MLOps, including CI/CD, pipeline automation, model retraining, and version control tools.
• Expertise in building large-scale data infrastructure, pipelines, and ETL systems.
• Knowledge of AI/ML governance frameworks, model monitoring practices, and handling model drift.
• Experience with Docker, Kubernetes, and IaC.
• Hands-on experience with containerization and orchestrating real-time systems.

Preferred Skills:

• Azure or AWS Certified.
• Experienced in Azure DevOps, ADF, metadata-driven pipelines, Azure Data bricks, ARM templates, and Azure Functions.
• Automotive, Healthcare, E-commerce, or Fintech.
• Battery systems
• IoC
• IoT sensor data for predictive modeling or connected vehicle solutions