Senior Machine Learning Engineer

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Take ownership and deliver machine learning-powered product features from start to finish — encompassing data pipelines, model integration, serving, monitoring, and iterative improvements in production.

• Collaborate closely with Scientists to transform research outputs into dependable, user-facing features.

• Develop and sustain ML infrastructure, including model serving, inference pipelines, LLM integrations, and evaluation frameworks.

• Participate in technical design discussions and architectural decisions within your team, gradually increasing your influence across other teams.

• Work alongside product software engineers to ensure seamless integration of ML capabilities into the overall product experience.

• Enhance the reliability, performance, and cost-effectiveness of the ML systems you manage — proactively identifying and resolving issues.

• Guide and mentor junior engineers through code reviews, collaborative work, and knowledge sharing.

⛳️ Requirements

• Over 5 years of experience in software engineering, with a significant emphasis on ML engineering, MLOps, or developing ML-powered products.

• Proficient in Python; familiarity with Ruby is an advantage.

• Robust experience in building and operating ML systems in production, including model serving, inference pipelines, and monitoring.

• Experience in integrating LLMs into production systems—covering prompt engineering, evaluation, or multi-provider setups.

• Proficient in SQL and data infrastructure — capable of working with data pipelines, transformations, and ensuring data quality.

• Experience with containerized deployments (Docker, Kubernetes) and cloud infrastructure (AWS).

• Proven ability to own features end-to-end and deliver them to production with a high standard of quality.

• Comfortable working in uncertain environments and adaptable to changing priorities.

• Strong collaborative skills — effectively working with scientists, product engineers, and product managers.

• Preferred experience with Snowflake and dbt for data transformations and analytics.

• Hands-on experience with ML pipeline tools (e.g., Metaflow) and experiment tracking systems (e.g., MLflow).

• Familiarity with model serving frameworks (e.g., BentoML) on Kubernetes.

• Knowledge of ML frameworks such as PyTorch or TensorFlow.

• Experience with event-driven architectures (e.g., Kafka).

• Familiarity with iterative, metrics-driven product development practices (A/B testing, feature flags, incremental rollouts).

🏝️ Benefits

• Flexible working hours

• Professional development opportunities