AI Jobs in Singapore

View detail

Design and deliver production-grade AI agents that are central to Sierra's growth, ensuring they are highly performant, reliable, and scalable in production environments across industries such as finance, healthcare, and commerce. Drive the Agent Development Life Cycle (ADLC) with complete ownership and autonomy from initial pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production and defining ADLC best practices. Partner directly with leaders at large enterprises and cutting-edge startups to understand their business challenges and build AI agents that transform operations at scale. Build the future of Sierra's platform by gathering customer feedback, prototyping new tools and features, and collaborating with research, product, and platform teams to enhance AI agent development and Sierra's product. Work on projects including designing AI agents to manage subscription churn, developing agents for complex customer interactions, creating industry-specific AI agent frameworks, facilitating design partnerships for new product initiatives, and experimenting with latest voice models for enterprise-grade integration.

View detail

Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, driving revenue directly to Sierra's growth. Take complete ownership of the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices. Partner directly with leaders of large enterprises and cutting-edge startups to understand business challenges and build AI agents that transform operations at scale. Work with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape the future of AI agent development and Sierra's product.

View detail

Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, running in production environments across industries like finance, healthcare, and commerce. Drive the Agent Development Life Cycle (ADLC) with complete ownership and autonomy from pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production and defining ADLC best practices. Partner with large enterprises and startups to understand business challenges and build AI agents that transform operations at scale. Build the future of Sierra's platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape AI agent development and product evolution.

View detail

As an Applied AI Engineer, you will be responsible for building and shipping AI features end-to-end, from model to system to user experience. This includes designing and iterating on prompts, tools, memory, and agent workflows, turning raw model outputs into structured and predictable behaviors, debugging issues across the full stack including model, orchestration, infrastructure, and user experience, optimizing for latency, cost, and production reliability, developing lightweight evaluation frameworks to measure real-world performance, and working closely with product and engineering teams to translate ambiguous problems into working systems. You will own problems end-to-end from shaping model behavior to building the surrounding systems to ensure reliable production performance.

View detail

Develop high-quality documentation, tutorials, and sample code to enable developers to effectively understand and utilize Mistral AI's products and integrations. Contribute to the community by resolving issues, providing answers, and offering guidance to users, fostering a supportive and collaborative environment. Lead developer relations initiatives and develop programs to engage the community. Organize and participate in community events centered around Mistral AI solutions. Work closely with the AI community to develop and maintain integrations, ensuring seamless compatibility and optimal performance. Remain informed about industry trends, best practices, and emerging technologies in AI, continuously updating your knowledge and skills.

View detail

Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement. Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer value. Synthesize and deliver valuable feedback to the Product and Research teams, turning real usage patterns into reproducible evaluations, benchmarks, and technical artifacts to improve model and product quality and influence roadmap and model development. Build repeatable tools, patterns, and evaluation approaches to raise quality across multiple use cases. Operate with strong judgment in ambiguous environments, balancing immediate technical problem-solving with longer-term system improvement. Build relationships within the startup ecosystem as a technical partner to both individual customers and the broader community. Create technical presentations, demos, and community engagement events with top developers and startups.

View detail

The role involves leading the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. It includes exploring the intersection of computer vision and robotic control to design systems that allow robots to perceive and interact with objects in dynamic environments. Responsibilities include creating models that integrate visual data to guide physical manipulation, collaborating with a multidisciplinary team to translate concepts into deployable robotic capabilities, researching and developing deep learning architectures for visual perception and sensorimotor control, designing algorithms for manipulating complex or deformable objects with precision, optimizing and deploying prototypes onto robotic hardware, evaluating model performance in simulation and real-world environments for robustness, identifying opportunities to apply advancements in computer vision and robot learning to industrial problems, and mentoring junior researchers while contributing to the technical direction of the research roadmap.

View detail

Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

View detail

Contributors may design graduate- and industry-level automotive engineering problems grounded in real practice; evaluate AI-generated solutions for correctness, assumptions, and engineering logic; validate analytical or numerical results using Python (NumPy, SciPy, Pandas); improve AI reasoning to align with first principles and accepted engineering standards; and apply structured scoring criteria to assess multi-step problem solving.

View detail

Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation for sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Work with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.