Mid/Senior Machine Learning Engineer (Time series) 

Permanent employee, Full-time · Hybrid IT, Turin

40,000 - 60,000 € per year

Overview

Joining AIKO means becoming part of a young, talented team dedicated to delivering high-quality work while maintaining a healthy work-life balance. We believe in trust, responsibility, and flexibility, offering a supportive environment where you can thrive. Our team enjoys collaborating in our Torino office, working from home when desired, and taking time off when needed. Don’t miss the chance to revolutionize the future with us! 

We are seeking a Machine Learning Engineer specializing in Time series analysis to join our growing and dynamic team. As a Mid/Senior Machine Learning Engineer specializing in Time Series, you will be instrumental in the development and optimization of machine learning models with a strong focus on time series analysis, anomaly classification, and predictive modeling. You will leverage your strong coding expertise to build efficient, high-performance models while utilizing MLOps to ensure seamless integration into production environments. You will work closely with a team of data scientists and ML engineers on groundbreaking projects that push the boundaries of AI integration in space technologies for health monitoring applications. Your expertise will directly impact our advanced time series-based services, supporting R&D projects and product development. 

Your role will be vital in refining our methodologies, workflows, and ensuring our models are robust and production-ready. 

We value smart, motivated, and collaborative engineers who love solving problems and making a difference. Time series analysis experience is essential, but what matters most is your passion for technology, drive to innovate, and commitment to contributing to cutting-edge solutions in the future of space health monitoring and anomaly detection solutions.

Tasks

Develop, implement, and optimize machine learning and deep learning models specifically tailored for, but not limited to, time series data to extract actionable insights for predictive maintenance and health monitoring applications. 
Build models to predict equipment failures, detect anomalies, and classify operational health patterns, ensuring proactive maintenance and minimizing downtime.
Actively be involved in new features design and development for health monitoring and predictive maintenance use cases, contributing to product innovation and enhancement.
Utilize Python, C++, and relevant ML libraries (e.g., PyTorch, TensorFlow) to develop, train, and deploy deep learning models, emphasizing high performance and reliability. 
Manage and handle large datasets, ensuring efficient data preprocessing and analysis, storage, and access for ML model training and evaluation.  Preprocess large-scale time series data, ensuring proper feature extraction, handling missing values, and ensuring high-quality data for training and evaluation of ML models.
Continuously improve model accuracy and performance, applying best practices in software quality, version control, and testing. 
Process, analyze, and visualize data, generating detailed reports, maps, and presentations for various stakeholders. 
Contribute to the development and deployment of machine learning models in production environments, leveraging MLOps approaches to ensure efficient integration and smooth operations. 
Work closely with cross-functional teams to deliver high-quality project outcomes, emphasizing accurate data handling, technical excellence, and adherence to deadlines. 
Stay updated on the latest advancements in time series data processing, machine learning, and deep learning technologies, promoting continuous learning within the team.

Requirements

MSc or PhD in Computer Science, Engineering, Mathematics,  or related fields. 
3-5 years of proven experience in machine learning and deep learning with a focus on time series analysis and predictive modeling.
Proven expertise in developing machine learning models for time series data, including data preprocessing, feature extraction, and model deployment.
Strong experience with object-oriented programming and a commitment to quality and achieving project goals. 
Exceptional coding skills in Python and C++, with a deep understanding of object-oriented programming and proven experience deploying ML models in production environments. Proficiency in Python and relevant ML libraries (e.g., PyTorch, TensorFlow, Pandas, Scikit-learn).
Strong statistical and analytical skills, with a solid grasp of machine learning theory and practical application. 
Excellent communication skills with the ability to present complex data insights to both technical and non-technical audiences. 
A proactive approach to problem-solving, with a strong commitment to goals, quality, and a positive attitude toward growth and change.

Preferred Experience

PhD in Computer Science, Engineering, Mathematics, or related fields, highlighting advanced expertise in machine learning applications. 
Previous working experience in a software product-oriented company.
Proven track record in key technical or lead roles in R&D projects, particularly in innovative or cutting-edge technology environments. 
Demonstrated success in managing ML projects focused on predictive maintenance or health monitoring from concept to deployment.
Expertise in designing and implementing MLOps pipelines using tools like Git, MLFlow, Kubeflow, and Kubernetes, ensuring efficient deployment of ML models. 
Demonstrated success in managing and scaling complex ML projects from concept to deployment, with proven integration into real-world applications. 
Extensive experience in data management practices and the ML software development lifecycle, emphasizing quality, scalability, and efficiency. 
Familiarity with Scrum working methodology and Agile principles, demonstrating an ability to work efficiently within iterative and collaborative development processes.

Benefits

Ticket Restaurants 
Health insurance, on a CCNL insurance plan
Welfare plan, according to CCNL
Flexible working hours 
Flexible smart working policy 
Access to courses for skills improvement 
Salary for the role: 40K-60K€

Hiring Process: 
The interview process for this role will somewhat look like: 

1st Stage: Interview with our People & Talent and the Hiring Manager 
2nd Stage: Technical step
We hopefully make you an offer!

DEI in AIKO

AIKO is an equal-opportunity employer. We encourage candidates from all  
backgrounds and experiences to apply. 

Research shows that women or people belonging to minorities often don't apply to  
roles they don't feel they match 100% of the requirements. If this posting is  
interesting to you, we encourage you to apply even if it is not a perfect match! We are  
looking for real people, not robots! 

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About us

AIKO is a cutting-edge deep-tech company founded in 2017. We specialize in developing advanced automation software tailored for space missions, empowering humanity's ambitions beyond Earth's orbit. Our mission is to revolutionize the space industry by providing innovative solutions that enhance efficiency, reliability, and safety in space exploration endeavors.

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Thank you for your interest in joining AIKO's team! We kindly ask you to fill in the sessions below to evaluate your application.