DATA Lead ML Ops Engineer (Korean + Japanese Speaker)
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Job Location:
Monthly Salary:
Posted on:
11 hours ago
Vacancies:
1 Vacancy
Job Summary
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way youd like where youll be supported and inspired bya collaborative community of colleagues around the world and where youll be able to reimagine whats possible. Join us and help the worlds leading organizationsunlock the value of technology and build a more sustainable more inclusive world.
Job Description
Duties and Responsibilities:
- MLOps engineer with 7-10 years of experience in ML model deployment for a client based in Korea. The MLOps engineer will be willing to work on location for the duration of the project (6-12 months) returning to Japan on completion.
- Design and implement CI/CD pipelines for training testing and deploying ML models.
- Build and maintain scalable ML infrastructure using cloud platforms AWS and some exposure to containerization (Docker Kubernetes).
- Experience moving models from research to production ensuring efficient scalable and reliable deployment.
- Continuously monitor model performance data drift accuracy and resource usage in production setting up alerts. Improve ML pipelines for efficiency cost-effectiveness and performance.
- Experience leading a team and/or work with data scientists (model requirements) and software engineers (integration) preferred.
Job Description - Grade Specific
Requirements and Qualifications:
Key Skills & Tools:
- Programming (Python).
- Cloud: Azure.
- Containerization (Docker Kubernetes).
- CI/CD Tools (Jenkins GitLab CI Argo).
- Knowledge of / Openness to learn: Domino Datalabs for MLOps.
- Language: Korean (business level - must) Japanese (N2 or higher) English (business)
Nice to Haves:
- Experience with AWS (EKS Sagemaker Step Functions) and hybrid/multi-cloud patterns.
- Hands-on with model observability tools (e.g. Evidently Prometheus/Grafana OpenTelemetry).
- Security and compliance in ML (secrets management IAM encryption audit).
- Experience with feature stores model registries and experiment tracking (e.g. Feast MLflow).
- Cost optimization of training/serving workloads; GPU/accelerator-aware scheduling.
- Experience integrating with enterprise data platforms (e.g. SAP Snowflake).
Soft Skills:
- Strong collaboration and stakeholder management across Data Science Platform and Application teams.
- Clear slide-making written and verbal communication; ability to simplify complex technical topics for non-technical audiences.
- Proactive ownership bias for automation and continuous improvement mindset.
- Mentorship of junior engineers and championing engineering best practices.
Educational Profile:
- Bachelors degree in Computer Science Software Engineering Data Engineering or related field; Masters or equivalent industry experience is a bonus.
Capgemini is an AI-powered global business and technology transformation partner delivering tangible business value. We imagine the future of organizations and make it real with AI technology and people. With our strong heritage of nearly 60 years we are a responsible and diverse group of 420000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem leveraging our capabilities across strategy technology design engineering and business operations. The Group reported 2024 global revenues of 22.1 billion.
Make it real
Required Experience:
IC
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
A global leader in consulting, technology services and digital transformation, we offer an array of integrated services combining technology with deep sector expertise.
