Job description

Description • Deploy & Automate: Own deployment automation from model handoff to live serving on Google Cloud Platform, successfully integrating models into Java-based streaming pipelines. • Benchmark & Evaluate: Assess new ML inference frameworks, conduct performance/quality testing, and perform model sampling to support researcher feedback loops. • Monitor & Debug: Track real-world model behavior and troubleshoot issues across the full distributed stack. • Collaborate: Partner closely with ML researchers to guide inference decisions, requiring enough core ML knowledge to establish a strong technical handshake. • 10+ years of engineering experience with a strong foundation in ML inference, deployment, and quality testing Requirements • Exposure to Java or JVM-based systems (model integration happens in Java, but deep expertise is not required). • Familiarity with streaming data architectures. • Experience operating in hybrid cloud and on-premises environments. Job responsibilities • Demonstrated ability to learn and adapt rapidly to non-standard or unfamiliar technologies. • Hands-on experience deploying models in cloud environments (Google Cloud Platform preferred). • Working knowledge of distributed systems sufficient for effective end-to-end testing and debugging. • Core ML knowledge to effectively benchmark models and collaborate with researchers. • Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field. GlobalLogic estimates the starting pay range for this role to be performed remotely to be $130,000 to $140,000 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. 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 About GlobalLogic GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.

Requirements

Must-haves

Deploy & Automate: Own deployment automation from model handoff to live serving on Google Cloud Platform, successfully integrating models into Java-based streaming pipelines.
Benchmark & Evaluate: Assess new ML inference frameworks, conduct performance/quality testing, and perform model sampling to support researcher feedback loops.
Monitor & Debug: Track real-world model behavior and troubleshoot issues across the full distributed stack.
Collaborate: Partner closely with ML researchers to guide inference decisions, requiring enough core ML knowledge to establish a strong technical handshake.
10+ years of engineering experience with a strong foundation in ML inference, deployment, and quality testing
Exposure to Java or JVM-based systems (model integration happens in Java, but deep expertise is not required).
Familiarity with streaming data architectures.
Experience operating in hybrid cloud and on-premises environments.
Demonstrated ability to learn and adapt rapidly to non-standard or unfamiliar technologies.
Working knowledge of distributed systems sufficient for effective end-to-end testing and debugging.
Core ML knowledge to effectively benchmark models and collaborate with researchers.
Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

Nice-to-haves

Hands-on experience deploying models in cloud environments (Google Cloud Platform preferred).

Application prep

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Keywords to mirror

javaml

Platform: globallogic
Effort: medium

Benefits

Benefits detected in the listing.

401k

Pto

Professional Development