Generative AI Engineer

1 week ago

Mississauga, Ontario, Canada Altimetrik Full time $120,000 - $180,000 per year

Altimetrik delivers outcomes for our clients by rapidly enabling digital business & culture and infuse speed and agility into enterprise technology and connected solutions. We are practitioners of end-to-end business and technology transformation. We tap into an organization's technology, people, and assets to fuel fast, meaningful results for global enterprise customers across financial services, payments, retail, automotive, healthcare, manufacturing, and other industries. Founded in 2012 and with offices across the globe, Altimetrik makes industries, leaders and Fortune 500 companies more agile, empowered and successful.

Altimetrik helps get companies get "unstuck". We're a technology company that lives organizations a process and context to solve problems in unconventional ways. We're a catalyst for organization's talent and technology, helping teams push boundaries and challenge traditional approaches. We make delivery more bold, efficient, collaborative and even more enjoyable.

Gen AI Engineer

  • 8 to 15 years (Senior)
  • 2-5 yrs Experience with any metadata tools such as Abinitio MHub, Alation
  • 2-5 yrs experience building the ML/AI models in banking environment where tooling can be used only from pre-approved inventory
  • Design and implement safety measures for Gen AI/ML systems to restrict unintended activities.
  • 7-12 yrs of experience with Java, Python, Pyspark, Go, Hadoop, Scala
  • 5-10 yrs of experience with XML, XSD, CSV, Parquet, Message queue, Hive, Impala
  • 4-6 yrs of epirience with Cloud Technonologies - AWS or Azure,
  • 5-7 yrs of experience with building AI/ML model from scratch, fine-tuning parameters, model validations
  • 7-8 yrs of experience with building end-to-end application surrounding the AI/ML (Including UI if needed)
  • Work collaboratively with Devs for positive and negative weight impact to train the model
  • Work team of Model developers to distribute and collectively deliver outcome
  • Strong understanding of model governance, compliance, and AI safety in enterprise environments
  • Experience with MLOps for deployment, monitoring, and maintenance of AI/ML models.

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