Why GMF Technology?
Innovation isn't just a talking point at GM Financial, it's how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We're committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.
Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.
What Makes You an Ideal Candidate?
Education and Experience:
What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), training, GM employee auto discount, community service pay and nine company holidays.
Our Culture: Our team members define and shape our culture. We have an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work - we thrive.
Compensation: Competitive salary and bonus eligibility
Work Life Balance: Flexible hybrid work environment, 2-days a week in office
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About the Role:
We are expanding our efforts into complementary data technologies for decision support in areas of ingesting and processing large data sets. Our interests are in enabling data science and search based applications on large and low latent data sets in both a batch and streaming context for processing. To that end, this role will incorporates aspects of software engineering and operations, combining SRE and DevOps skills to come up with efficient ways of managing and operating applications. The role will require a high level of responsibility and accountability to deliver technical solutions. The data sets we deal with support both off-line and in-line machine learning training and model execution. Other data sets support search engine based analytics. Exploration and deployment of technologies activities include identifying opportunities that impact business strategy, selecting data solutions software, and defining hardware requirements based on business requirements. Responsibility also includes documentation of procedures for deployment, monitoring, managing and switching the environments in production and disaster recovery sites. This role participates along with team counterparts to architect an end-to-end framework developed on a group of core data technologies
About the Role:
We are expanding our efforts into complementary data technologies for decision support in areas of ingesting and processing large data sets. Our interests are in enabling data science and search based applications on large and low latent data sets in both a batch and streaming context for processing. To that end, this role will incorporates aspects of software engineering and operations, combining SRE and DevOps skills to come up with efficient ways of managing and operating applications. The role will require a high level of responsibility and accountability to deliver technical solutions. The data sets we deal with support both off-line and in-line machine learning training and model execution. Other data sets support search engine based analytics. Exploration and deployment of technologies activities include identifying opportunities that impact business strategy, selecting data solutions software, and defining hardware requirements based on business requirements. Responsibility also includes documentation of procedures for deployment, monitoring, managing and switching the environments in production and disaster recovery sites. This role participates along with team counterparts to architect an end-to-end framework developed on a group of core data technologies