OmnixDrive 人才招募

高级人工智能工程师｜智能驾驶数据与模型研发

公司简介

OmnixDrive 是一家成立于 2026 年、总部位于新加坡的人工智能初创科技公司，专注于智能驾驶底层人工智能技术与基础设施研发。技术方向涵盖大规模驾驶数据处理、深度学习模型训练与优化、视觉感知、多传感器融合及算法工程化，为智能驾驶系统提供底层技术支持。

招聘信息

• 招聘人数： 3–5 名
• 工作模式： 混合办公，可远程协作或根据项目需求现场工作
• 协作时区： UTC+8（新加坡时间）
• 合作形式： 项目制合作

岗位职责

1. 设计和开发智能驾驶数据处理体系，包括数据清洗、筛选、标注、增强及训练数据集构建。
2. 研发视觉感知算法，涉及目标检测、图像分割、目标跟踪及三维环境感知。
3. 负责深度学习模型的设计、训练、微调与优化，提升模型精度、鲁棒性及泛化能力。
4. 参与摄像头、激光雷达、毫米波雷达等多源传感器数据处理与融合。
5. 优化模型训练流程、计算资源利用率、推理效率及部署性能。
6. 独立负责核心技术模块，解决复杂算法与工程问题，按项目要求完成交付。

任职要求

1. 10 年以上软件开发经验，其中至少 5 年机器学习、深度学习或智能驾驶人工智能研发经验。
2. 具备扎实的计算机科学、数学及机器学习基础，深入理解神经网络和模型训练机制。
3. 精通 Python，熟练使用 PyTorch 或 TensorFlow；具备 C++ 开发能力者优先。
4. 具备大规模训练数据处理经验，熟悉数据清洗、标注、增强、样本筛选及质量评估。
5. 在目标检测、语义分割、目标跟踪或三维感知等计算机视觉方向具备深入研发经验。
6. 具备完整的模型训练与优化经验，能够独立完成模型设计、训练、参数调优及性能评估。
7. 能够解决模型过拟合、训练不稳定、长尾场景识别及模型泛化能力不足等问题。
8. 熟悉模型部署、推理优化及 GPU 计算资源管理，具备独立技术攻关和项目交付能力。

优先条件

• 具备自动驾驶或高级辅助驾驶系统研发经验。
• 熟悉鸟瞰视角感知、占用网络、三维目标检测及多目标跟踪技术。
• 具备摄像头、激光雷达及毫米波雷达多传感器融合经验。
• 熟悉 Transformer、卷积神经网络及视觉基础模型。
• 具备大规模驾驶数据管理、自动化标注及数据闭环建设经验。
• 熟悉 CUDA、TensorRT、ONNX、分布式训练及模型量化、推理加速技术。
• 具备量产级智能驾驶系统或实际道路场景研发经验。

合作与报酬

采用项目制合作，报酬根据项目规模、技术难度、工作量及交付要求协商，可按项目阶段或交付成果结算。优秀人才可获得长期合作机会。

申请方式

请将个人简历发送至：

careers@omnixdrive.com

申请材料请注明工作年限、技术专长、相关项目经历、个人技术贡献、模型研发经验、期望项目报酬及可投入时间。

官网： https://OmnixDrive.com

OmnixDrive — 以人工智能驱动下一代智能出行。

OmnixDrive Careers

Senior AI Engineer – Autonomous Driving Data & Model Engineering

About OmnixDrive

OmnixDrive is a Singapore-based AI technology startup established in 2026, specializing in foundational AI technologies and infrastructure for intelligent driving. Its technical focus includes large-scale driving data processing, deep learning model training and optimization, visual perception, multi-sensor fusion, and algorithm engineering.

Position Overview

• Openings: 3–5
• Work Arrangement: Hybrid, with remote collaboration and on-site work depending on project requirements.
• Collaboration Time Zone: UTC+8 (Singapore Time)
• Engagement: Project-based

Key Responsibilities

1. Design autonomous driving data pipelines, including data cleaning, filtering, annotation, augmentation, and dataset construction.
2. Develop perception algorithms for object detection, image segmentation, tracking, and 3D environment understanding.
3. Train, fine-tune, and optimize deep learning models to improve accuracy, robustness, and generalization.
4. Develop data processing and fusion solutions for cameras, LiDAR, and radar.
5. Optimize training workflows, computing resources, inference efficiency, and deployment performance.
6. Lead core technical modules and deliver solutions to complex algorithmic and engineering challenges.

Requirements

1. 10+ years of software engineering experience, including at least 5 years in machine learning, deep learning, or autonomous driving AI development.
2. Strong foundations in computer science, mathematics, and machine learning, with an in-depth understanding of neural networks and model training.
3. Expert proficiency in Python and hands-on experience with PyTorch or TensorFlow. C++ experience is preferred.
4. Proven experience in large-scale training data processing, including cleaning, annotation, augmentation, sample selection, and quality assessment.
5. Substantial experience in at least one computer vision area, such as object detection, semantic segmentation, tracking, or 3D perception.
6. End-to-end model development experience, covering architecture design, training, hyperparameter tuning, and performance evaluation.
7. Ability to diagnose and resolve overfitting, training instability, long-tail recognition, and generalization issues.
8. Experience in model deployment, inference optimization, and GPU resource management, with strong independent problem-solving and delivery capabilities.

Preferred Qualifications

• Experience in autonomous driving or advanced driver-assistance systems.
• Knowledge of BEV perception, occupancy networks, 3D object detection, and multi-object tracking.
• Experience in camera, LiDAR, and radar sensor fusion.
• Familiarity with Transformer architectures, CNNs, and vision foundation models.
• Experience in large-scale driving data management, automated annotation, and data-loop infrastructure.
• Knowledge of CUDA, TensorRT, ONNX, distributed training, model quantization, and inference acceleration.
• Experience with production-grade autonomous driving systems or real-world road applications.

Engagement & Compensation

This is a project-based engagement. Compensation will be negotiated according to project scope, technical complexity, workload, and delivery requirements. Payments may be arranged by project milestones or deliverables. Long-term collaboration opportunities are available.

How to Apply

Please send your CV/Resume to:

careers@omnixdrive.com

Please include your professional experience, technical expertise, relevant projects, individual contributions, model development experience, expected project compensation, and availability.

Website: https://OmnixDrive.com

OmnixDrive — Driving the Future of Intelligent Mobility Through AI.