About the Role
Challenge yourself and us. At AdvanceWorks, we learn together, grow together, and have fun together. And we do all this while creating great software solutions for clients across many industries and geographies. We are constantly challenging ourselves and each other to use the latest technologies and the best methodologies and make sure we walk the talk.
Responsibilities
•Working closely with Data Scientists to bring machine learning services and models into production.
•Designing, developing, and maintaining robust and scalable web APIs to serve machine learning models.
•Developing frameworks and reusable technical solutions for recurring machine learning problems.
•Promoting the adoption of common frameworks and engineering practices that accelerate the delivery of machine learning solutions at scale.
•Contributing to the design and implementation of machine learning pipelines, from data collection and processing strategies to model training, evaluation, deployment, and inference.
•Developing and maintaining production-grade inference services and supporting their integration with other systems.
•Collaborating with DevOps, Software Architecture, and Platform teams to design scalable and reliable ML solutions.
•Working with cloud platforms and cloud-native services to support machine learning workloads and production deployments.
•Contributing to data processing solutions using technologies such as Spark, Beam, or Flink.
•Working with streaming and messaging platforms, particularly Kafka, where applicable to ML and data pipelines.
•Contributing to the automation of infrastructure and processes for training, evaluating, and deploying machine learning models.
•Implementing unit tests and following software engineering best practices throughout the development lifecycle.
•Using Git and established build and release processes to ensure reliable software delivery.
•Contributing to containerized solutions using Docker and Kubernetes.
•Monitoring, troubleshooting, and continuously improving production ML services and supporting infrastructure.
•Contributing regularly to the documentation of systems, frameworks, tools, APIs, and technical processes.
•Promoting knowledge sharing and the reuse of solutions across projects and departments.
•Participating in technical discussions and contributing to architectural and engineering decisions.
Requirements
•Professional experience in software development and machine learning engineering.
•Strong programming skills in at least one object-oriented programming language, such as C# or Java.
•Professional experience with Python and familiarity with its use in data science and machine learning environments.
•Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, and/or Scikit-Learn.
•Clear understanding of the machine learning lifecycle, from data preparation and model development to evaluation, deployment, and inference.
•Experience with data processing technologies such as Spark, Beam, Flink, or similar.
•Experience with cloud platforms such as Azure, AWS, or GCP.
•Good knowledge of SQL and/or other query languages such as Spark SQL.
•Experience working with NoSQL databases such as MongoDB, Redis, Cassandra, or similar.
•Experience with containerization technologies such as Docker and Kubernetes.
•Familiarity with streaming and messaging platforms such as Kafka.
•Experience with software build and release processes, unit testing, source control, and software development best practices.
•Strong experience with Git and collaborative software development practices.
•Good scripting skills and a solid understanding of Linux/Unix command-line environments.
•Ability to develop scalable and maintainable APIs and backend services.
•Strong focus on software quality, reliability, maintainability, and automation.
•Passion for Machine Learning and AI and an interest in applying these technologies to real-world problems.
•Collaborative and proactive mindset, with the ability to work effectively across different technical teams.
•Excellent written and verbal communication skills, with the ability to communicate effectively with different stakeholders, including Product and Engineering teams.
•Good understanding of Agile methodologies.
•Availability to work in a hybrid model, with 3 days per week in Oeiras.
Benefits
•An amazing informal culture of smart, hardworking, and friendly people who support and care about each other.
•A mentorship program from day one.
•The opportunity to work with real-world operational data from tolling and Intelligent Transportation Systems.
•The opportunity to work on large-scale data and cloud projects using modern technologies.
•Formal training and certifications in data, cloud, and engineering excellence.
•Access to cutting-edge tools and technologies.
•A dynamic company where your ideas matter more than job titles.
•Flexibility with responsibility.
•A Rubber Duck to help you debug those tricky data pipelines.
