Senior Machine Learning Engineer
Senior Machine Learning Engineer
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Salary Not Disclosed
1 Vacancy
Job Description
Get to know the Team
The mission of the ML Pipeline team at Grab is to empower machine learning engineers data scientists data analysts and data engineers to testandlearn their ideas and productionise them at scale. The team develops tools systems and automation to increase productivity throughout the ML and AI development lifecycle.
Get to know the Role
As a Machine Learning Engineer in our ML Pipeline team you will be responsible for contributing to the design implementation and rollout of cuttingedge ML&AI platforms for largescale workloads at Grab.
The Critical Tasks You Will Perform
Write productiongrade code perform code reviews and ensure exceptional code quality
Build robust lasting and scalable products Iterate quickly without compromising quality
Setup and define standards for complex pipelines including data engineering feature engineering model training model quality verification model deployment etc.
Automate cloud infrastructure provisioning and deployments of ML pipelines
Qualifications :
What Essential Skills You Will Need
A bachelors/Master degree in computer science machine learning or related fields
3 years of machine learning experience in industry
Proficient in at least one programming language such as Golang Python Scala or Java
Strong understanding of machine learning approaches and algorithms
Extensive knowledge of ML frameworks such as TensorFlow PyTorch Spark ML scikitlearn or related frameworks
Experiences of Docker Kubernetes Ray NoSQL solutions Memcache/Redis cloud platforms (specifically AWS)
Familiarity with machine learning lifecycle management including feature engineering model training validation deployment A/B testing monitoring and retraining
Experienced in MLOps and managing production machine learning lifecycle is a plus
Experience developing machine learning models for ranking recommendations search content understanding image generation or other relevant applications of machine learning is a plus
Prior working experience with building GenAI or llmops platforms is a plus
Additional Information :
Our Commitment
We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best regardless of nationality ethnicity religion age gender identity or sexual orientation and other attributes that make each Grabber unique.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
