Senior data scientist

Job Description

The individual will be contributing to a specialized AI initiative focused on developing an intelligent agent that interacts with email content. The project also includes exploratory work in video and audio modalities, with the goal of expanding the agent's capabilities beyond text-based communication to multimodal understanding and response.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and 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. 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.