AI engineer in ML pipelines

Accenture Portugal; Lisboa; Hybrid; EUR 27,000 - 48,000; Full time

Benefits offered by this job

Health insurance

Life insurance and pension plan

Office medical services

Wellness programs

Flexben program

Employee stock purchase plan

Training paths and Udemy access

Flex-ability program

Special banking conditions

Hybrid working model

Job summary

Accenture Portugal is seeking a data-centric professional to support operation and troubleshooting of data and ML pipelines in production. You will validate data, collaborate via Git and notebooks, and help monitor and improve batch and streaming pipelines on Azure with PySpark and Spark.

The role requires 1-3 years of experience, strong English, and the ability to work across distributed teams in an Agile environment.

Qualifications

• Bachelor's or master's degree in Computer Science, Engineering, or a related field.
• 1-3 years of relevant work experience.
• Experience with Git, notebooks, data validation, and SQL is a must.
• Basic experience with Python and ML/AI concepts; exposure to data or AI environments.
• Familiarity with Azure services (Synapse, Data Lake, Databricks).
• Awareness of monitoring concepts (logs, alerts).
• Interest in CI/CD and DevOps practices.
• Professional English (C1 level).
• Strong communication and collaboration in distributed teams.
• Must own valid work permit or EU/Schengen nationality.
• French or Dutch is a plus.

Responsibilities

• Support operation and troubleshooting of data and ML pipelines in production.
• Perform data validation and sanity checks to ensure data quality.
• Use Git to collaborate on code changes and follow version control best practices.
• Assist in monitoring systems using logs and basic alerts.
• Assist in building and maintaining batch and streaming pipelines using Spark / PySpark.
• Support CI/CD pipelines and DevOps practices for data and ML workloads on Azure.
• Collaborate with backend, platform and AI engineers in distributed teams.
• Contribute to data and AI solutions using Python, SQL, JSON/YAML and Git.
• Implement and inspect pipelines on Azure and use notebooks to test logic.
• Use ML experimentation tools (MLflow, Weights & Biases, Databricks ML) to support model validation.
• Apply data validation and anomaly detection.
• Support pipeline execution, troubleshooting and safe rerun practices.
• Ensure observability through logs and alerts.
• Follow Agile delivery and documentation practices.
• Maintain awareness of model lifecycle concepts.

Skills

Git

Python

SQL

Spark / PySpark

Azure

Data validation

Notebooks

Education

University degree in Computer Science or related field

Tools

Azure Synapse

Azure Data Lake

Databricks

MLflow

Weights & Biases

Job description

Описание

At Accenture Digital Core, we help clients continuously innovate at speed and at scale, combining deep industry expertise with cutting-edge technology to deliver meaningful transformation. You will bring innovation, intelligence and experience together to shape robust, secure and scalable digital solutions.

Задачи

• Support the operation and troubleshooting of data and ML pipelines in production;


• Perform data validation and sanity checks to ensure data quality and reliability;


• Use Git to collaborate on code changes and follow version control best practices;


• Assist in monitoring systems using logs and basic alerts;


• Assist in building and maintaining batch and streaming pipelines using Spark / PySpark;


• Support CI/CD pipelines and DevOps practices for data and ML workloads on Azure;


• Collaborate with backend, platform and AI engineers in distributed and cross-functional teams;


• Contribute to data and AI solutions using Python, SQL, JSON/YAML and Git;


• Implement and inspect pipelines on Azure and use notebooks to test logic and support model inputs;


• Use ML experimentation tools (MLflow, Weights & Biases, Databricks ML) to support model validation and analysis;


• Apply data validation, sanity checks and basic numerical precision awareness to detect inconsistencies and anomalies;


• Support pipeline execution, basic troubleshooting and safe rerun practices;


• Ensure observability through basic log and alert interpretation;


• Apply secure data handling principles and adhere to compliance constraints;


• Follow Agile delivery and documentation practices;


• Maintain awareness of model lifecycle concepts, assumptions and limitations.

Требования

• University degree in Computer Science, Software Engineering, Information Technology, Engineering, or a comparable technical field;


• 1-3 years of relevant work experience;


• Experience with Git (version control), Notebooks (e.g. Synapse), Data validation / sanity checks and SQL is a must;


• Basic experience with Python and basic understanding of ML/AI concepts Exposure to data or AI environments (academic, internship or early professional experience);


• Familiarity with Azure services (Synapse, Data Lake, Databricks);


• Awareness of monitoring concepts (logs, alerts);


• Interest in CI/CD and DevOps practices;


• Professional English (C1 Level required in spoken and written);


• Effective communication with both technical and non‑technical stakeholders;


• Strong collaboration skills within distributed and cross‑functional teams;


• Proactive mindset with a high sense of ownership and accountability;


• Structured approach to incident and problem management;


• Ability to prioritize workload efficiently in a dynamic environment.; Must own a valid work permit or EU/Schengen Space Nationality to legally work in Portugal Будет плюсом: French or Dutch is a plus

Условия

• Health insurance;


• Life Insurance and Pension Plan Programs;


• Free medical services at the office (Physician, Nutritionist, Psychologist);


• Wellness programs;


• Flexben Program (Support for Education, Kindergarden, Training, Technology, Health);


• Employee Share Purchase Plan;


• Personalized training paths and access to Udemy and Plurisight Plataforms;


• Flex-ability program (financial and flexible support for people with disabilities);


• Special banking conditions;


• Hybrid working model.