Data Scientist

Summary

Join our team as a Data Scientist in Portugal and contribute to the development of AI-powered decision-making systems, enhancing our Recommender System and making smarter decisions based on complex data inputs.

Requirements

• Bachelor’s or Master’s degree in a quantitative discipline such as Data Science, Computer Science, Engineering, or a related field
• Minimum of 5+ years of experience as a Data Scientist, with at least 2+ years of experience in MLOps and ML model deployment at scale
• Proven expertise in deploying machine learning models for large-scale production environments and monitoring their performance for multiple clients or business units
• Hands-on experience with MLOps tools such as Airflow, and cloud-based solutions (GCP Vertex AI)
• Proficiency in Python for deep learning model development and deployment (mandatory)
• Proven experience with Deep Learning and Reinforcement Learning for building machine learning models at scale (mandatory)
• Experience with NoSQL databases (e.g., MongoDB) and JSON for handling Big Data and real-time applications
• Experience working with Recommender Systems
• Experience working with TensorFlow Recommender System (TFRS) and Two Towers architecture is a plus
• Experience with model monitoring, performance tracking, and A/B testing in production environments to ensure continuous improvement and accuracy
• Expertise in implementing scalable and automated CI/CD pipelines for machine learning models, including model versioning and retraining workflows
• Strong knowledge of containerization and orchestration tools such as Docker and Kubernetes
• Experience working with Large Language Models (LLMs), such as Gemini or ChatGPT-4, to build intelligent systems (mandatory)
• Understanding of data engineering concepts, including ETL pipelines, data lakes, and big data platforms (BigQuery, Snowflake, Redshift)
• Strong teamwork and collaboration skills, with a focus on working across departments to achieve project success

Responsibilities

• Drive the design, development, and deployment of machine learning models, with an emphasis on the Recommender System, ensuring scalability and robustness for handling large datasets and multiple clients
• Collaborate with data engineers and ML engineers to implement MLOps best practices, ensuring seamless integration of models into production pipelines, including both batch and real-time predictions, automated model retraining, versioning, and monitoring
• Oversee the operationalization of models, including real-time predictions, batch processing, and retraining pipelines, especially for the Recommender System
• Monitor model performance post-deployment, implementing metrics and alerts to track model drift, accuracy degradation, and data changes
• Build and maintain continuous integration (CI) and continuous deployment (CD) pipelines to ensure models are rapidly and reliably updated in production
• Ensure the model serving infrastructure is optimized for performance, resource utilization, and cost efficiency, leveraging GCP
• Work closely with product managers and stakeholders to define and refine ML model objectives, translating business needs into model requirements
• Implement automated testing, validation, and documentation of models to ensure they meet performance and accuracy standards before deployment
• Act as a key technical advisor on AI and ML initiatives, working with the team to share best practices in AI, MLOps, and model deployment, while contributing to the AI-powered decision-making systems to integrate customer data with external factors (e.g., weather, location, and time of day)
• Use Large Language Models (LLMs), such as Gemini, to enhance and develop AI-driven features within our platform
• Work collaboratively with cross-functional teams, ensuring teamwork and communication are key aspects of problem-solving and project success

Preferred Qualifications

• Experience with multi-tenant ML platforms, serving models to multiple clients with different data and needs (preferred)
• Familiarity with DevOps and cloud infrastructure, especially utilizing serverless technologies such as GCP Functions or AWS Lambda
• Experience working with natural language processing (NLP) or computer vision models in production

Benefits

• Health insurance: Tillster pays the premium for employee private health insurance. Employees have the option to add their spouse/dependents at the employee’s cost
• Holidays: Up to 20 federal and local/municipal holidays in accordance with applicable Portuguese Labour laws, dependent on your employment start date
• Vacation: Up to 22 days of vacation every holiday year, pro-rated based on employment start date
• Meal allowance for each day worked available through meal card
• Home/Office allowance reimbursement per calendar month, pro-rated based on employment start date
• Education, Learning & Development: We offer Udemy Learning courses; and ongoing learning and development opportunities