Senior Machine Learning Engineer
Grab
Company Description
About Grab and Our Workplace
Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.
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 test-and-learn 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 Senior Machine Learning Engineer in our ML Pipeline team, you will be responsible for designing, implementing, rolling out, and evangelizing cutting-edge ML&AI platforms for large scale workloads at Grab.
You will report to the Senior Machine Learning Engineering Manager and work onsite at our office based in Petaling Jaya
The Critical Tasks You Will Perform
- Write production-grade code, at scale
- Develop platform applications from infrastructure to frontend in full stack
- 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
- Reason about how to use appropriate frameworks, algorithms, and data structures
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, scikit-learn, 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
- Strong collaboration, mentorship and communication skills
Additional Information
Life at Grab
We care about your well-being at Grab, here are some of the global benefits we offer:
- We have your back with Term Life Insurance and comprehensive Medical Insurance.
- With GrabFlex, create a benefits package that suits your needs and aspirations.
- Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
- We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
- Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours
What We Stand For At Grab
We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.
