Machine Learning Engineer

MAKE HISTORY WITH US!

At PMI, we’ve chosen to do something incredible. We’re totally transforming our business and building our future on smoke-free products with the power to build a smoke-free future.

With huge change, comes great opportunity. So, wherever you join us, you’ll enjoy the freedom dream up and deliver, better, brighter solutions and the space to move your career forward in endlessly different directions

Role Overwiev

As a Machine Learning Engineer, you will apply advanced data science techniques to analyze data and ML models, assessing and fine-tuning them for optimal business and technical performance. This role requires deep understanding of ML frameworks and techniques, including data exploration and manipulation. You will be working with both structured and unstructured data, utilizing specialized programming languages and tools to drive effective decision-making and create business value.

WHO ARE WE LOOKING FOR?

• You have a master’s degree in Data Science, Computer Science, Statistics or a related field.
• 3 + years of experience in a data science or related role.
• Proficient in at least one of the following languages: Python, R, SAS or Julia.
• Strong knowledge of machine learning algorithms, techniques and libraries (eg. TensorFlow, PyTorch)
• Experience with data pre-processing, feature engineering and model evaluation
• Ideal candidates will have experience working with Snowflake, Docker, Kubernetes, AWS: S3, EMR and SageMaker.
• Recommended: Experience with Atlassian Suite (Bitbucket/JIRA/Confluence)
• Proven understanding and addressing ethical implications and biases in models, analytical and critical thinking, problem-solving, innovative thinking to develop new models and approaches.
• Experience working directly with remote technical teams
  
  

HOW CAN YOU MAKE HISTORY WITH US?

• Develop, train, and deploy machine learning models assessing them for performance, robustness, and bias. Choose appropriate metrics to evaluate outcomes. Identifying and resolving issues both before and after model deployment.
• Anticipate and address ethical, bias, privacy, and data protection implications of ML/AI models. Establish traceability for outcomes produced by ML models.
• Maintain thorough documentation of data science processes, models, and experiments to ensure reproducibility and knowledge sharing.
• Provide data-driven insights and recommendations to support strategic business decisions and initiatives while also identifying opportunities for process optimization and automation, striving for continuous improvement in data management practices.
• Finally, you will actively anticipate and resolve potential data issues before they escalate, demonstrating a proactive approach to data.
  
  

Please note that only online applications will be taken into consideration. Only selected candidates will be contacted.

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