Machine Learning Engineer (MLOps)

Work from home - Machine Learning Engineer (MLOps)

Your role:

We are looking for a highly capable Senior MLOps Engineer with a strong Software Engineering and DevOps background. As a Senior MLOps Engineer, you will be embedded and supporting a revenue generation or cost optimization project, ensuring its success in production by improving the code, creating automated CI/CD testing, and developing frameworks that can be reused for other similar projects.

 

• Build, maintain, and document machine learning frameworks (python packages) used across multiple projects.
• Support a project team with Data Scientists, Business Stakeholders, Analysts, and Data Engineers.
• Develop reusable feature stores for rules-based and AI/ML models.
• Implement monitoring capabilities for model performance and effectiveness in production.
• Automate CI/CD testing and deployments incorporating MLOps best practices.

 

Required:

• Bachelor's degree in software engineering, computer science, data science, mathematics, or a related field.
• 5+ years of overall experience in Data Analytics.
• 3+ years of experience with ML Engineering and/or ML Ops. Up to 2 years of Software Engineering or Data Engineering experience can also count towards this requirement.
• Sharp critical thinking skills and ability to learn and question complex processes and solutions.
• Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
• Experience creating python packages
• Well-developed software engineering skills, including use of proper development, QA, and production environments, object-oriented programming, version control, and knowledge of multiple programming languages.
• Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
• Proficiency in SQL.

 

Preferred Requirements:

• Master’s or PhD degree in computer science, data science, mathematics, or a related field.
• Experience with sensor data or other noisy data types.
• Experience with Agile Software Development.
• Experience in a large corporation or consulting firm with focus in marketing strategies, modeling, CRM and management sciences/statistics highly desired.
• Familiarity with frameworks and languages designed for big-data analytics, including Spark and Azure Data Factory.
• Experience with MLOps and ML experiment tracking tools, such as Azure DevOps and MLFlow or similar.
• Experience with cloud computing services such as Microsoft Azure, Amazon Web Services and/or Google Cloud Platform.
• Familiarity with different data science techniques: statistics, machine learning, or cognitive AI.

 

What We Offer

• Stable Employment: Permanent contract offering long-term job security.
• Learning & Development: Access to a wide range of online training platforms and professional development resources.
• Language Training: Weekly virtual English classes and conversation sessions with certified instructors. Online Courses for different languages.
• Health Coverage: Comprehensive prepaid medical and dental plans.
• Insurance Protection: Life and accident insurance for peace of mind.
• Wellness Perks: Discounts and benefits through fitness and technology partnerships.
• Special Occasion benefits.

 

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Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications. 1. Applies scientific methods to analyse and solve software engineering problems. 2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance. 3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers. 4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities. 5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.