Senior Machine Learning Engineer

Job Description

You will be part of a strategic initiative focused on developing predictive maintenance algorithms for a client’s manufacturing operations. The solution aims to detect equipment issues before failures occur, improving uptime, reducing costs, and boosting efficiency.

Built on advanced data science and MLOps practices, and using rich time-series data from industrial machinery, the platform will deliver actionable insights fully integrated into existing engineering workflows.

Responsibilities

• Lead technical delivery : Drive the development of pipelines for transforming raw sensor data using time-windowing, FFT, and domain-specific features. Ensure scalable, high-quality data processing aligned with best practices and reproducibility standards
• Shape architecture : Design and implement anomaly and failure detection models, both unsupervised (Isolation Forest, One-Class SVM) and supervised (XGBoost, Random Forest), ensuring robust and compliant architectures while staying current with relevant frameworks
• Collaborate across roles : Bridge data science, engineering, and domain teams to align on requirements and delivery plans. Support RUL forecasting with time-series models like LSTM, ensuring outputs are clear and actionable
• Ensure delivery excellence : Apply explainable AI tools (LIME, SHAP) and create diagnostic visualizations to build trust and transparency. Maintain strong experiment tracking, versioning, and deployment using MLflow for reliable production workflows
• Mentor and support : Guide the team through the ML lifecycle, secure deployments, and monitoring. Provide mentorship, support onboarding, and encourage technical growth and consistency

Qualifications

Additional Information

At Accesa you can :

Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.