Job Summary
- Technical Skill:
- Machine Learning ,
- Python ,
- PyTorch ,
- Docker ,
- Kubernetes
Job description
Overview of job
We're seeking a Machine Learning Engineer to build and deploy multi-agent conversational AI systems with voice capabilities. You'll be responsible for developing real-time voice agents that can engage in natural, multi-turn conversations while maintaining high performance at scale.
Responsibilities
- Design and implement multi-agent voice-based AI systems that can handle complex, real-time conversations
- Build and optimize streaming communication pipelines for real-time speech processing
- Deploy and scale ML models for production environments
- Optimize model serving and inference for high-performance requirements
Technical Requirements
Multi-Agent Systems & Voice AI
- Experience building multi-agent systems using LLMs
- Knowledge of voice agent architectures and conversation management
- Understanding of multi-turn dialogue systems
- Knowledge of interruption and end turn detection in voice interaction, mimicking human-like conversation flow.
Streaming & Real-time Processing
- Strong experience with async/streaming architectures
- Proficiency in building real-time communication systems
- Experience with WebSocket, gRPC, or similar streaming protocols
- Hands-on experience with speech processing pipelines
Production ML Experience
- Track record of deploying ML systems to production
- Experience with ML monitoring and observability
- Understanding of ML system scalability and reliability
- Understanding of deploying ML/DL models on a large scale setup (optimize latency / throughput/ GPU usage…)
- Experience with at least one serving framework such as Ray, Triton Server, Kubeflow,..
- Competitive compensation package, including 13th-month salary and performance bonuses
- Comprehensive health care coverage for you and your dependents
- Generous leave policies, including annual leave, sick leave, and flexible work hours
- Convenient central district 1 office location, next to a future metro station
- Onsite lunch with multiple options, including vegetarian
- Grab for work allowance and fully equipped workstations
- Fun and engaging team building activities, sponsored sports clubs, and happy hour every Thursday
- Unlimited free coffee, tea, snacks, and fruit to keep you energized
- An opportunity to make a social impact by helping to democratize credit access in emerging markets.
Job Requirement
Requirements
- BS/MS in Computer Science or related field
- 3+ years of ML engineering experience
- Most prioritize to strong python coding skills, strong logical thinking, strong debugging, tracing open source code
- Experience with PyTorch or similar ML frameworks
- Demonstrated experience shipping production ML systems (Docker, k8s,..)
This role combines ML engineering with real-time voice processing expertise, focusing on building practical, scalable AI systems that can be deployed in production environments.
Languages
-
English
Speaking: Intermediate - Reading: Intermediate - Writing: Intermediate
Technical Skill
- Machine Learning
- Python
- PyTorch
- Docker
- Kubernetes
COMPETENCES
- Logical Thinking
BUSINESS PROFILE
Trusting Social is a Fintech AI company.
Trusting Social is a Fintech AI company who pioneers alternative credit scoring for emerging markets using telecom data and other new data sources. We aim to provide credit scores for 1 billion unbanked consumers who currently do not have access to formal credit. We target emerging markets worldwide, with the initial focus on Southeast Asia and India.
Trusting Social is comprised of Ph.D. data scientists from Stanford Research Institute, Microsoft, IBM etc., and banking leaders from Goldman Sachs, Credit Suisse, and Barclays. Founded in Silicon Valley, Trusting Social is now headquartered in Singapore, with R&D lab in Ho Chi Minh, and offices in Hanoi, Manila, and Jakarta.