Overview
Skills
Job Details
Role Title: Senior Data Scientist - Generative AI / LLM / Agentic AI / Computer Vision
Employment Type: Contract;Contract-to-Hire
Duration: 6 month contract with extensions. Possibility for hire
Preferred Location: Remote, no preference on time zone
Role Description:
We're seeking a Senior Data Scientist with deep, hands-on expertise in Generative AI, Large Language Models (LLMs), Agentic AI, and Computer Vision. The ideal candidate has a strong track record of designing and deploying AI models in production at scale, including work on both text-based and image-based AI systems. A solid background in traditional machine learning, predictive modeling, and proficiency in cloud platforms such as Azure and Databricks is essential.
Key Responsibilities:
- Design and deploy scalable LLM, Generative AI, and Agentic AI systems in production environments.
- Build and refine computer vision models (e.g., object detection, image segmentation, image captioning, visual reasoning).
- Develop end-to-end AI pipelines: data collection, preprocessing, training, evaluation, deployment, and monitoring.
- Apply traditional machine learning methods to solve predictive modeling problems across structured and unstructured data.
- Integrate AI solutions with enterprise platforms using Azure, Databricks, and distributed systems.
- Collaborate with data engineers, MLOps teams, and product stakeholders to align solutions with business needs.
- Continuously improve model performance and reliability through testing, monitoring, and feedback loops.
Requirements:
Required Qualifications:
- 5+ years of experience in data science and applied machine learning.
- 2+ years of direct experience building and deploying LLMs and Generative AI models in production.
- Experience developing agentic AI solutions, such as tool-using agents or autonomous workflows at scale.
- Expertise in computer vision, with hands-on experience using frameworks like OpenCV, PyTorch, Detectron2, or YOLO.
- Proficient in both traditional ML (e.g., classification, regression, clustering, time series) and deep learning approaches.
- Skilled in Python and common ML/AI libraries (Transformers, Hugging Face, TensorFlow, LangChain, etc.).
- Strong communication and collaboration skills, including translating complex models into actionable business insights.