Open role, R&D
Machine Learning
Engineer
The engineering that keeps AI running. Data pipelines, deployment, monitoring and cost, with Google Cloud as the home platform.
Pipelines, deployment and MLOps on Google Cloud
This seat owns the path from raw data to a model running in production and staying there. Ingestion and ETL, training and deployment pipelines, monitoring, and the cost of it all, built on Google Cloud and expected to survive contact with real client volumes.
Most AI work fails on this side rather than on the modelling side. A pipeline that breaks quietly, a model that drifts without anyone noticing, an inference bill nobody modelled: those are the problems this role exists to prevent. The work is judged on whether something keeps working when you are not watching it.
Google Cloud is our preferred cloud and the platform you will spend most of your time in. Above it we stay model-agnostic on purpose, privileging three families, Anthropic, Google Gemini and OpenAI, which from this side of the work is an architecture problem before it is a preference: what gets abstracted, what gets pinned, and how a solution survives a model being deprecated or a new one, Mythos, Gemini Enterprise, Astra, being worth moving to.
That also means building generative AI as a system rather than a single call. Several models chained or routed, each doing the step it is suited to, and connected to agentic no-code or low-code automation wherever that is the shorter honest path. Your part is making that whole arrangement observable, repeatable and affordable.
You will work across clients and industries alongside the rest of the tech hub, on solutions that are expected to reach production rather than stop at a proof of concept.
What you will actually do
- ML SolutionsResearch, design, and implement machine learning solutions in customer engagement, customer experience and sales ecosystems.
- OperationalizationDevelop and operationalize AI solutions, from data collection and processing to model deployment and monitoring.
- Data Pipelines & ETLBuild and maintain the ingestion and transformation layer on Google Cloud, so that what reaches a model is current, clean and traceable.
- Productization FrameworksBuild and maintain scalable frameworks for productizing ML and AI-based software, ensuring performance and efficiency.
- ExperimentationDevelop projects across data feeds, integrations, digital assistants, NLP, hyper-personalization, sentiment analysis, predictive analytics, recommendations, predictive lead scoring, multivariate testing and LLM-powered assistants.
- Monitoring & CostInstrument what you deploy: drift, failure modes, latency and spend, so that a model degrading in production is noticed by a dashboard and not by a client.
- Cross-Functional IntegrationCollaborate with engineering, marketing and product teams to integrate ML and AI solutions, with a market-first, data-driven, iterative approach.
- DocumentationDocument Gen AI, ML and DL frameworks, algorithms and innovations for knowledge sharing across the team.
- IP & ComplianceDevelop innovative solutions that comply with ethical guidelines, data privacy laws and industry best practices.
Technical & platform skills
- Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics or a related field, preferred.
- Experience
- 2 to 5 years developing and deploying machine learning solutions, with real time spent on the production side rather than only in notebooks.
- Programming
- Expertise in Python or another relevant programming language, with strong software engineering practice: version control, testing and continuous integration.
- Data work
- Experience with data modeling, unstructured data transformation, cleaning, preprocessing, feature engineering, analytics engineering and ETL, with scikit-learn, pandas or Spark MLlib.
- Cloud
- Experience in Google Cloud, Azure or AWS, with Google Cloud as our working default.
- AI literacy
- Literacy in Tech and AI subjects, and practical understanding of how LLMs and agents work: context, tools, memory, and why the same prompt can return different answers. Sophisticated use of AI platforms, both with efficiency and security.
- Languages
- English and Portuguese.
- Multi-model architecture
- Comfort serving more than one model family behind a single solution, Anthropic, Google Gemini and OpenAI above all, with the abstraction, routing and fallback that keeps a swap from becoming a rewrite.
- Agentic automation
- Enough exposure to agentic no-code and low-code tooling to connect it to what you deploy, and the judgement to know when it is the right layer and when it is a liability.
Behavioral skills
- Analytical Thinking
- Analytical and problem-solving skills applied to messy, real data rather than clean examples.
- Technical Bridge
- Ability to bridge communication between technical and business teams.
- Collaborative Spirit
- Collaborative and team-oriented approach, in a hub that works across clients and industries.
- Continuous Learning
- Desire for continuous learning and professional growth in a fast-paced environment.
- Ownership
- Accountability for what runs in production, including the parts that are not interesting.
- Kindness
- At Wise Pirates we promote and admire kindness, independently of rhythm, intensity and efficiency.
- AI Readiness
- Interest and fluency in using AI as a partner to deliver efficient value, respecting security and privacy regulations.
- Innovation Lover
- Someone seeking continuous growth and desiring to be part of innovative solutions.
Not required. Noticed.
- Professional experience in AdTech or Martech, or in an R&D lab in a university or private setting.
- Deep knowledge of generative AI, LLMs, TensorFlow, PyTorch and LangChain, with JAX, Keras, FastAI, Transformers or DeepSpeed as a plus.
- Professional experience with Google Cloud services: Vertex AI, Dataflow, BigQuery, Cloud Storage, Composer, Generative AI Studio, Model Garden, Gemini.
- Professional experience with MLOps tools such as MLflow, Kubeflow, SageMaker, DVC or TFX.
- Experience with low-code and no-code ecosystems and workflow automation.
- Knowledge of agile methodologies, or postgraduate studies in Data Science.
- Additional years of experience beyond the range above, for more ownership over platform decisions.
- Depth in generative AI and agent systems, which is the neighbouring seat’s core and a strong complement here.
A Digital, Tech and AI Business Partner
Wise Pirates is a leading Digital, Tech, and AI Business Partner, operating from Portugal. With a team of 100+ professionals, we are a Martech-independent agency at the forefront of innovation in Southern Europe. Our ambition is to lead an AI-first marketing ecosystem, blending human creativity with the power of artificial intelligence.
We are dynamic, forward-thinking, and driven by data, automation, and meaningful customer experiences. We believe that our people are our most valuable asset, and we are committed to fostering a culture where they can grow, innovate, and thrive.
Our value proposition is holistic and new generation. We combine services with proprietary products, custom data and proprietary frameworks, so the client gets one capability aimed at their business results, not a stack of separate disciplines. You get to work across all of it.
The part most
job ads skip
- A front-row seat in a growing agency placing AI at the centre of how we work and how we serve our clients, both in service and products. Senior peers in every discipline, our sharpest edge and your fastest growth.
- A culture of autonomy connected to a clear orientation towards action and performance. You own your projects end-to-end and have real space to grow. The rhythm is intense and evolution happens at a fast pace.
- Direct exposure to a wide range of use cases, industries, and clients across 80+ countries, with real impact on what gets shipped.
- Continuous learning alongside a cross-functional team of automation, data, media, and creative specialists.
Why join the navy when you can be a pirate?
Portugal, hybrid, full time. Direct client impact from day one, alongside senior peers in every discipline.
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