Engineer

Job Description

Responsibilities

• Rapid Prototyping & Innovation: Don’t just use open-source codeinnovate on top of it. Experiment with the latest libraries to build novel solutions for complex logistics challenges.
• End-to-End Ownership: Translate abstract business requirements into logical, scalable AI architectures. You will own the solution from data analysis to model deployment.
• Performance Engineering: Its not enough to be accurate; it must be fast. Diagnose, troubleshoot, and optimize inference pipelines for low latency and high throughput.
• Data-Centric AI: Drive the strategy for Data Analysis, Feature Engineering, and Augmentation. You will guide the annotation team and build pipelines to extract meaningful insights from massive Vision and Text datasets.
• Advanced Vision & NLP: Build robust solutions for Person/Scene understanding (Pose Estimation, Re-Identification) and integrate GenAI/LLM capabilities to add semantic understanding to visual data.
• Cross-Functional Collaboration: Work closely with the DevOps and Product teams to translate AI needs into effective, fault-tolerant technical solutions.
• Technical Leadership: Experience leading AI/Computer Vision projects, making architecture decisions, conducting code reviews, and mentoring engineers to deliver production-ready solutions.
• Engineering Management: Experience managing technical teams, allocating resources, setting development priorities, conducting performance reviews, and supporting career growth.

Skills & Requirements

• Production Python: Strong experience writing clean, modular, and fault-tolerant code. You understand that a model in a notebook is not a product.
• Deep Learning Stack: Proficiency in PyTorch is essential and experience with inference optimization tools like TensorRT is also required. Experience with practical edge deployement is a massive plus.
• Custom Model Training: Familiarity with training or fine-tuning custom AI models (Detectors, Classifiers) from scratch.
• Computer Vision Mastery: Deep understanding of Image Processing technologies (OpenCV, Dlib, NumPy) and modern architectures (YOLO, ResNet, etc.), OCRs and VLMs.
• NLP & GenAI: Hands-on experience with Hugging Face, LangChain, and NLP libraries (Spacy, NLTK). Ability to implement RAG pipelines or Agentic workflows.
• Complex Vision Tasks: Experience with advanced problems like Person Re-Identification, Pose Estimation, and Tracking.
• Applied AI: A proven track record of successfully applying machine learning to solve real-world problems (not just Kaggle competitions).
• Team Management: Experience managing and growing high-performing engineering teams, conducting code reviews, defining development processes, and fostering a culture of engineering excellence.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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