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Machine Learning Engineer (GCP)GlobalLogic • San Jose, Arizona, United States
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Machine Learning Engineer (GCP)

GlobalLogic
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
Jetzt Bewerben

Über

Primary platform: Google Cloud Platform (inference, deployment automation, experimentation, sampling)
Infrastructure: Hybrid — on-premise streaming + GCP serving stacks
Distributed systems: Working knowledge required for debugging and end-to-end testing (not deep expertise)
Machine Learning frameworks: TensorFlow, PyTorch, JAX or similar
Requirements
Evaluate and benchmark new ML inference frameworks to guide production decisions
Deploy models to GCP and integrate them into production applications and Java-based streaming pipelines
Own deployment automation end-to-end — from model handoff through live serving
Monitor how models behave in production for real end-users.
Design and execute benchmarking, performance testing, and quality testing on ML models
Perform model sampling to support quality evaluation and researcher feedback loops
Debug issues across the full stack — from inference layer down to streaming pipelines.
Partner with ML researchers to provide benchmarking feedback and guide inference decisions — requires enough core ML knowledge to have a meaningful technical handshake
Adapt rapidly to non-standard and evolving tech stacks across hybrid (on-prem + GCP) infrastructure.
Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.
Disclaimer: GlobalLogic estimates the starting pay range for this role to be performed remotely to be $125,000 to $135,000 and reflects base salary only. This pay range is provided as a good-faith estimate, and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.
Job responsibilities
Strong foundation in ML inference, deployment, and quality testing
Demonstrated ability to ramp up quickly on new and unfamiliar tech stacks — this is the single most important trait
End-to-end problem-solving mindset — can own a problem from model handoff to user-facing behavior
Core ML knowledge sufficient to benchmark models and collaborate with researchers
Experience deploying models in cloud environments, ideally GCP.
Exposure to Java or JVM-based systems (model integration happens in Java; deep expertise not required)
Familiarity with streaming data architectures
Experience in hybrid cloud/on-prem environments.
What we offer
Exciting Projects: Come take your place at the forefront of digital transformation! With clients across all industries and sectors, we offer an opportunity to work on market-defining products using the latest technologies.
Collaborative Environment: You can expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities!
Work-Life Balance: GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules and opportunities to work from home.
Professional Development: We provide continuing education classes, professional certification and training (technical, soft skills, language, and communication skills) to help you realize your professional goals. Being part of a global organization, there are additional learning opportunities through international knowledge exchanges.
Excellent Benefits: We provide our employees with competitive salaries, health and life insurance, short-term and long-term disability insurance, a matched contribution 401K plan, flexible spending accounts, and PTO and holidays.
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  • San Jose, Arizona, United States

Sprachkenntnisse

  • English
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