1 day ago
Beijing, ChinaStaff+
Responsibilities
- Architect and implement offline, model-based, and simulation-based reinforcement learning pipelines for pricing, dispatch, and supply repositioning.
- Design latent world models and spatio-temporal marketplace state representations for complex supply-demand interactions.
- Establish off-policy evaluation frameworks, conservative value-estimation baselines, and safety guardrails for production deployment.
- Build behavioural simulation systems using fine-tuned open-source large language models.
- Partner with backend, streaming, and platform engineering teams to deploy low-latency decision agents in high-throughput production environments.
- Lead technical strategy for a specialized team of scientists and engineers and accelerate team workflows using generative-AI development tools.
Requirements
- PhD in Computer Science, Operations Research, Applied Mathematics, or a related quantitative discipline with at least 10 years of post-degree experience leading complex machine learning research and production initiatives, or a Master’s degree with 12+ years of equivalent experience.
- Proficiency in reinforcement learning foundations, including Markov Decision Processes, stochastic control, offline reinforcement learning, and reward shaping for sequential multi-objective decision systems.
- Proven experience deploying production ML or RL systems under real-time constraints, non-stationary data, and distribution shifts.
- Hands-on expertise adapting and aligning large language models using supervised fine-tuning, parameter-efficient methods such as LoRA and QLoRA, and preference tuning such as RLHF, DPO, or GRPO.
- Hands-on proficiency in Python, PyTorch, and distributed training or compute platforms such as Ray, DeepSpeed, FSDP, or Megatron-LM.
- Experience using AI tools and emerging technologies to improve productivity, workflows, and technical innovation.
Benefits
- Term Life Insurance and comprehensive Medical Insurance.
- GrabFlex benefits package customization.
- Parental leave, Birthday leave, and Love-all-Serve-all volunteering leave.
- Confidential Grabber Assistance Programme.
- FlexWork arrangements with differentiated hours.
- Full-time onsite work at Grab’s Beijing office.
Categories
About Grab
Grab builds a Southeast Asia superapp for mobility, deliveries, and financial services, serving consumers, drivers, merchants, and enterprises. It monetizes via ride and delivery commissions, merchant services (such as ads and subscriptions), and payments and digital banking products. Founded in 2012 and headquartered in Singapore, Grab operates across multiple Southeast Asian markets and is publicly listed on NASDAQ.