AI Engineer, AI Assistant
Job Description
Job Description:
- Agentic Workflow: Design and implement core Agent architectures and Agent tooling
- API integration & Deployment: Build and optimize API's for Agent lifecycle and deployment for runtime access.
- Memory & Tools: training optimization in Agent and Tool-use directions, improving metrics such as tool-calling accuracy, multi-turn instruction following, and hallucination control.
- Data & Evaluation: Manage the collection, cleaning, synthesis, and annotation workflows for post-training data participate in annotation guideline development and vendor coordination.
Requirements:
- Master's in Computer science, Engineering, Information systems, or a related field
- Minimum 1 Year of full time working experience in AI workflow design, RAG, workflow design and optimization for a user facing AI product.
- Minimum 1 Year of full time experience with multimodal agents and Reinforcement learning or model training.
- Experience with E-commerce platform and agents will be highly preferred.
Kindly note that you can only be considered for one role at a time with any of the companies within our Group. If you have applied for other jobs with the Group, you will be considered for roles in the order of your application
More Info
Job Type:
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Key Skills
model training
multimodal agents
Data Evaluation
Agent architectures
Agent tooling
Memory Tools
E-commerce platform
About Company
Skills:
Matplotlib, Natural Language Processing, Tensorflow, Numpy, Pandas, Pytorch, Gcp, Computer Vision, Azure, Python, AWS, Scikit-learn, reinforcement learning
Skills:
object detection , Dsp, C, Image Processing, Gpu, Tensorflow, Pytorch, Computer Vision, Linux, Opencv, Python, Isaac Sim, Tracking, Gazebo, perception pipelines, reinforcement learning, NPU, AI ML models, ROS2
Skills:
Machine Learning, Information Retrieval, Python, Function Tool Calling, SFT, DPO, Model Evaluation, reinforcement learning, Structured Generation, Recommendation Systems, GRPO-style Optimization, RL, Prompt Engineering
Skills:
Orchestration, Python, Context engineering, Embedding fine-tuning, Multi-agent LLM systems, Multi-agent collaboration, Recall ranking, RAG retrieval systems, Memory architectures, Task planning, Multi-turn dialogue management, Long-text processing, Multi-document synthesis, Quantitative evaluation systems, Tool calling, RL reward models
Skills:
Software Testing, Information Security, Jira, Sql, Performance Testing, Security Testing, Automation Testing, Api Testing, Data Testing, AI Testing, Model Evaluation, Hallucination Detection, Bias Fairness