Data science

Senior data science

We are looking for a Data Scientist with expertise in Computer Vision (primarily) and Large Language Models (LLMs) to help build, train, and optimize machine learning models for traffic video analysis and LLM-powered data retrieval systems. You will work on YOLO-based object detection models, training datasets, and scaling inference pipelines while also supporting LLM-based retrieval-augmented generation (RAG) applications

Key Responsibilities

• Design, train, and optimize computer vision models for traffic analytics using YOLO or similar frameworks.
• Work on LLM-powered systems, specifically for retrieval-augmented generation (RAG) applications that integrate traffic data with chatbot-like interfaces.
• Prepare, clean, and preprocess large-scale traffic video datasets for model training and inference.
• Implement train-test-validation workflows, hyperparameter tuning, and performance evaluation techniques.
• Enhance model generalization across various camera angles, lighting conditions, and motion blur scenarios.
• Collaborate with MLOps engineers to deploy models efficiently in AWS-based environments.
• Utilize Python-based deep learning frameworks (e.g., TensorFlow, PyTorch) and apply cloud computing best practices for model execution.
• Troubleshoot model performance issues, conduct error analysis, and iterate on improvements.
• Work in a startup environment, balancing agility, quick iteration cycles, and scalable solutions.

Required Qualifications

Deep Learning & Model Training: Strong background in computer vision (YOLO, OpenCV, object detection, classification, and segmentation).

Large Language Models (LLMs): Experience working with retrieval-augmented generation (RAG) and fine-tuning LLMs.

Data Processing & Pipeline Management: Ability to clean, preprocess, and structure large datasets (video-based and text-based).

Machine Learning Deployment: Experience integrating trained models into production systems.

Python & ML Frameworks: Proficiency in Python, TensorFlow or PyTorch for ML workflows.

AWS Cloud Computing: Familiarity with AWS-based ML workflows, including EC2, Lambda, and containerized model execution (Docker, Kubernetes, Terraform).

Strong Algorithmic & Analytical Thinking: Capable of hyperparameter tuning, performance evaluation, and debugging complex ML issues.

Adaptability & Startup Mindset: Comfortable working in a fast-paced, evolving environment with ambiguity and autonomy.

Nice-to-Have Qualifications

Experience working in computer vision applications for traffic analysis or similar domains

Previous startup experience, comfortable with quick decision-making and iterative model improvement.

Soft Skills & Work Culture Fit

Self-motivated and able to work independently in a remote setting

Strong problem-solving skills and ability to think outside of the box

Excellent communication skills to collaborate effectively with remote teams

Comfortable with quick iteration cycles and ability to pivot based on business needs

Experience working in small, fast-moving teams where agility and efficiency are key

Overlap Hours:

·    6-8 hours with EST (8 hours highly preferred)

Contract Length:

12 months, renewable

>Must have skills 

 Machine Learning

 AWS (Amazon Web Services)

 Retrieval-Augmented Generation (RAG)

 LLM (Large Language Models)

 Computer Vision

 Data Science

 SQL

 Python