Data Platform Developer, Machine Learning

Key Skills

Apache Airflow, Apache Flink, Apache Kafka, API, AWS Sagemaker, Big Data Technology, Data Architecture, Docker, Google BigQuery, Java Programming, Kubeflow, Kubernetes-K8s, Machine learning techniques, MLflow, Python Programming, PyTorch, Red Hat OpenShift, Scikit-learn, Spring Boot, TensorFlow

Job Description

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Platform Developer to develop and maintain new Machine Learning platforms. If you love technology, and are keen to join an industry leader — we would love to hear from you!

What you'll do:

The Data Platform Developer will be building a machine learning platform which supports the machine learning data pipelines and models lifecycle management for the data science team on Google Cloud Platform. This position will devise new methodologies and infrastructure for reconstructing and enriching data at scale, while supporting internal data scientists who leverage the big data environment to build, train, and deploy machine learning models. To be successful in this role you will be a self-starter with strong written and verbal communication skills, and have the ability to quickly understand complex, technical concepts.

How you’ll make an impact:

• Develop and maintain new machine learning platforms managing the data pipelines and machine learning model workflow for Geotab’s internal models. 

• Develop processes to enrich Geotab’s big data with telematics data at scale.

• Develop processes and implement logging, monitoring, and alerting services to ensure the health of Geotab’s machine learning platform and models.

• Work with data scientists to understand data processing needs and develop infrastructure solutions to support these initiatives.

• Create and maintain documentation for architecture, requirements, and process flows.

• Support internal Geotab teams to assist with data integration with newly developed big data platforms.

What you’ll bring to this role:

• Post-secondary Degree specialization in Computer Science, Software or Computer Engineering or a related field.

• 3-5 years experience in machine learning platform developer or a similar role. 

• 3-5 years experience in developing production-level systems using Python 3

• 3-5 years experience in Tensorflow, PyTorch, Scikit-Learn or similar machine learning frameworks

• 1-5 years experience in either cloud or on-premise machine learning workflow tools such as Vertex AI, SageMaker, Kubeflow, or MLflow.

• 1-5 years experience in designing, building and maintaining production-level application containerization, such as Docker, Kubernetes, or OpenShift.

• Knowledge of Apache Kafka, Apache Flink, Apache Ignite, or Apache Airflow is a big plus.

• Knowledge of Java and Spring Boot is a big plus.

• Knowledge of gRPC, Protobuf, Apache Avro, Apache Beam is a plus.

• Knowledge of data management fundamentals and data storage principles.

• Knowledge of batch and streaming data architectures.

• Experience with API design and implementation.

• Familiar with Big Data environments (e.g. Google BigQuery).

• Strong analytical skills with the ability to problem solve well-judged decisions.

• Highly organized and able to manage multiple tasks and projects simultaneously.

• Strong team player with the ability to engage with all levels of the organization.

If you got this far, we hope you're feeling excited about this role! Even if you don't feel you meet every single requirement, we still encourage you to apply.

Please note: Geotab does not accept agency resumes and is not responsible for any fees related to unsolicited resumes. Please do not forward resumes to Geotab employees.

Why job seekers choose Geotab:

• Work from home and flex work arrangements
• Home office reimbursement program
• Baby bonus & parental leave top up program
• Online learning and networking opportunities
• Electric vehicle purchase incentive program
• Competitive medical and dental benefits
• Retirement savings program

*The above are offered to full-time permanent employees only

How we work:

At Geotab, we have adopted a flexible first working model in that we have systems, functions, programs and policies in place to support both in-person and virtual work. However, you are welcomed and encouraged to come into our beautiful, safe, clean offices as often as you like. When working from home, you are required to have a reliable internet connection with at least 50mb DL/10mb UL. Virtual work is supported with cloud-based applications, collaboration tools and asynchronous working. The health and safety of employees are a top priority. We encourage work-life balance and keep the Geotab culture going strong with online social events, chat rooms and gatherings. Join us and help reshape the future of technology!

We believe that ensuring diversity is fundamental to our future growth and progress and is an integral part of our business. We believe that success happens where new ideas can flourish – in an environment that is rich in diversity and a place where people from various backgrounds can work together. Geotab encourages applications from all qualified individuals. We are committed to accommodating people with disabilities during the recruitment and assessment processes and when people are hired. We will ensure the accessibility needs of employees with disabilities are taken into account as part of performance management, career development, training and redeployment processes. If you require accommodation at any stage of the application process or want more information about our diversity and inclusion as well as accommodation policies and practices, please contact us at careers@geotab.com.