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
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