Senior Machine Learning Engineer at Itaú, driving innovation with data and AI solutions. Collaborating across teams to implement robust machine learning architectures and ensure scalable deployments.
About the role
- Platform Engineer developing API and CI/CD environments for machine learning at CADDi, improving developer productivity and system reliability.
Responsibilities
- Build API and batch execution environments for running machine learning model inference, as well as deployment environments using CI/CD.
- Implement monitoring, performance tuning, and other improvements to enhance site reliability in production environments.
- Optimize the cost of inference and training platforms.
- Create the deployment and operation processes based on input from the modeling and platform teams.
- Actively experiment with new ML, MLOps, and infrastructure tools, quickly validating ideas through proof-of-concepts and applying what works to real company products.
- Besides the team we are recruiting for this time, you may be assigned to other teams depending on your experience and preferences. (In that case, we would be happy to discuss this with you at the interview.)
- After joining the company, your role may change due to organizational growth or an individual's career perspective.
Requirements
- 5+ years of professional experience as a software engineer
- Experience leading software development
- We especially value experience leading design, development, operations, and the necessary communication involved in roles such as team lead or project driver, regardless of project size
- At least 2 years of experience in ONE or more of the following:
- Developing shared platforms or backend systems using cloud infrastructure.
- Designing and operating Machine Learning systems (MLOps) with consideration for latency, cost, and non-functional requirements.
- Developing Generative AI applications using LLMs, RAG architectures, and Vector Databases.
- Hands-on experience with statically typed programming languages (such as TypeScript, Rust, Java/Kotlin, Go, etc)
- General understanding of the core Computer Science concepts behind AI (such as Vector Space, Embeddings, or Inference) and the ability to leverage these principles to build and integrate AI-driven features into software platforms.
- Experience in development using public cloud platforms such as AWS, Google Cloud, etc.
- Fluent business communication skills in English, able to complete daily tasks in English, including text communication and meetings.（CEFR B1 or Higher level)
- Must currently reside in Vietnam or have plans to relocate. Foreign nationals must also hold a valid Vietnam work permit or be legally eligible to work in Vietnam.
- Experience developing machine learning pipelines using tools such as Vertex AI Pipelines, Kubeflow, Apache Beam, or Spark
- Familiarity with at least one ML/AI framework such as scikit-learn, PyTorch, or TensorFlow.
- Development experience related to MLOps or SRE
- Experience collaborating with ML engineers to continuously improve and deliver machine learning and data science models
- Experience building and operating systems such as Data Lakes or Feature Stores
- Experience implementing initiatives to improve data quality for data-centric ML model improvement
- Experience planning and driving data utilization initiatives—internally or externally—using tools such as BigQuery or Redash
- Basic knowledge of algorithms related to machine learning, statistics, linear algebra, and computer science
- Experience working with Scrum or Agile methodologies.
- Conversational-level Japanese proficiency(Japanese Language Proficiency Test N2 or above is a guideline)
Benefits
- Hybrid (come to Office at least once a week)
- Remote (depending on the case, and limited to those who can go on business trip due to Company orders)
- Office address:
- HCMC: 7F, Gia Loc Building, No. 27-29 Nguyen Cuu Van Street, Ward 17, Binh Thanh District, HCMC
- Hanoi: Unit 9.03, 9F, The West Building, 265 Cau Giay Street, Cau Giay Ward, Hanoi
- Official full-time employee
- Probation period: 2 months
- Annual paid leave: 12 days
- National holidays
- Year-end holidays (December 31 to January 3)
- Tet holidays
- Others (following Labor Regulations)
- 13th month salary
- Salary review: twice a year
- 100% monthly basic salary and mandatory social insurances in 2-month probation
- Premium Health Insurance
- Social insurance, health insurance, unemployment insurance, workers’ accident compensation insurance
- Annual health check-up
- Allowances such as: child-care allowance, commuting allowance, life event congratulatory gift, etc
- Growth support such as subsidy for server fee, support for attending external training courses
- Intensive training program (external or internal training courses, workshop etc)
- Devices: PC and display of desired specifications
- Awards: Company awards, every 6 month MVP awards
- Activities: Year-end-party, team building, etc
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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