At Bose, better sound is just the beginning. We’re passionate engineers, developers, researchers, retailers, marketers … and dreamers. One goal unites us — to create products and experiences our customers simply can’t get anywhere else. We are driven to help people reach their fullest human potential. Creating technology to help people to feel more, do more, and be more. We are highly motivated and curious, and we come to work every day looking to solve real problems and make the best experiences for our customers possible.
The Bose Data Engineering team is responsible for design, development and enhancement of Bose Data Platforms (Analytics & Customer Data Platforms) in leading and supporting Advanced Analytics & AI/ML workloads. This team is highly impactful and a key enabler of Bose Digital journey by playing a central role in the Data driven transformation.
What you will be working on?
As MLOps you will work closely with our Data Scientists to accelerate the AI/ML lifecycle, from data acquisition and model training to model deployment and monitoring. As part of an agile delivery team, you will design, develop, deploy and support the AI/ML pipelines, applying MLOps best practices and implementing the necessary integrations with our Data Platform ecosystem. This role requires knowledge and hands-on experience with data, ML and software deployment technologies.
- Improve and extend the AI/ML lifecycle, applying MLOps best practices and helping Data Scientists taking their models to production.
- Design and develop ML pipelines for connected devices, web applications, and mobile applications that support the customer experiences.
- Stay up to date on relevant technologies, plug into user groups, understand trends and opportunities that ensure we are using the best techniques and tools
- Collaborate with AWS Cloud Architects to optimize and evaluate scalable and serverless solutions.
- Work in multi-functional agile teams to continuously experiment, iterate and deliver on new data product objectives.
Qualifications (Demonstrated Competence)
- Degree in Computer Science (or equivalent).
- Experience with Amazon Web Services.
- Experience building CI/CD pipelines and monitoring.
- Proficient with Python and SQL.
- Knowledgeable about the Machine Learning lifecycle as part of overall MLOps focus of this role.
- You appreciate agile software processes, data-driven development, reliability, and responsible experimentation.
Highly Desirable But Not Required Skills Include
- You have previous experience supporting Data Science teams.
- You’ve built scalable ML pipelines using the AWS SageMaker ecosystem.
- You had contact with ML platforms such as Kubeflow, Vertex AI.
- You have worked with a variety of cloud and data solutions such as Snowflake, Kafka, Spark or Airflow.
Benefits & Perks
- Highly competitive benefit package
- State of the art technological environment
- Employee product discounts
- Create and shape our local company culture with the support of a fantastic global group
- Continuous training and career development