ML Engineer
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 leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization, and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
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