ML Engineer
6 miesięcy temu
1. Project description
Our leading customer is actively seeking collaboration to design a comprehensive target architecture for their MLOps environment and to establish a clear implementation roadmap. Grid Dynamics will assist the customer's team by leveraging their infrastructure accelerators to provision the initial ML platform on Google Cloud Platform (GCP) and to onboard the data science team effectively. The partnership will extend to developing end-to-end deployment automation for ML models, including the setup of associated infrastructure, IAM roles, and pipeline tooling. Additionally, Grid Dynamics will construct robust MLOps pipelines tailored to support the project's release cycles, validation processes, and requirements for version control and auditing. The project will also involve aiding the data science team in migrating ML models to the cloud, ensuring a seamless transition and operational excellence in the new environment.
Essential functions
Lead the design and implementation of sophisticated ML systems using Vertex AI. Optimize and maintain ML workflows for maximum efficiency and cost-effectiveness. Develop innovative solutions to complex business challenges using advanced ML techniques. Ensure the highest standards of data security and privacy compliance. Drive best practices in ML development and operations within the team.
Qualifications
Advanced Machine Learning Expertise : Deep knowledge of machine learning principles and algorithms, with proven experience in model tuning, optimization, and deployment. Proficiency with Vertex AI : Extensive hands-on experience in using Google Cloud Vertex AI for developing, deploying, and managing ML models. Strong Programming Skills : Expertise in Python and familiarity with ML libraries like TensorFlow, PyTorch, or scikit-learn. Experience in Cloud Architecture : Strong background in cloud solutions architecture, specifically with Google Cloud Platform (GCP), with a focus on building scalable and secure ML systems. Data Engineering Skills : Proficient in managing and manipulating large datasets, and experienced with GCP data services like BigQuery and Dataflow.
Personal and Professional Qualities
Excellent problem-solving and analytical skills. Strong leadership qualities and experience mentoring junior engineers. Excellent communication skills, capable of explaining complex technical details to non-technical stakeholders.
Would be a plus
Google Cloud Professional Machine Learning Engineer certification. Experience with full lifecycle ML project management, including stakeholder engagement, requirement gathering, system design, testing, and deployment. Familiarity with AI ethics and responsible AI practices.
We offer
Opportunity to work on bleeding-edge projects Work with a highly motivated and dedicated team Competitive salary Flexible schedule Benefits package - medical insurance, sports Corporate social events Professional development opportunities Well-equipped office
About us
Grid Dynamics (Nasdaq:GDYN) is a digital-native technology services provider that accelerates growth and bolsters competitive advantage for Fortune 1000 companies. Grid Dynamics provides digital transformation consulting and implementation services in omnichannel customer experience, big data analytics, search, artificial intelligence, cloud migration, and application modernisation. Grid Dynamics achieves high speed-to-market, quality, and efficiency by using technology accelerators, an agile delivery culture, and its pool of global engineering talent. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the US, UK, Netherlands, Mexico, and Central and Eastern Europe. To learn more about Grid Dynamics, please visit www.griddynamics.com. Follow us on Facebook, Twitter, and LinkedIn.
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