Data Scientist / AI-ML Engineer

Position Overview

We are seeking an experienced Data Scientist / AI-ML Engineer to join our team and help design, build, and deploy data-driven solutions. The ideal candidate will have hands-on experience with the full machine learning lifecycle – from data preparation and model development to deployment and monitoring – while collaborating closely with business and technical stakeholders.

Key Responsibilities

• Design and develop machine learning models, predictive analytics, and AI solutions for real-world business problems.
• Perform data collection, cleansing, and feature engineering to build high-quality datasets.
• Implement, train, test, and optimize ML algorithms (e.g., classification, regression, NLP, deep learning).
• Collaborate with cross-functional teams to translate business requirements into data science solutions.
• Develop and maintain data pipelines and model deployment frameworks (using tools such as Airflow, MLflow, or Docker).
• Communicate insights through visualizations, dashboards, and reports.
• Stay current with advancements in AI, ML, and data technologies and propose innovative applications.
• Support cloud-based AI implementations (Azure, AWS, or GCP).

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 5+ years of experience in data science, machine learning, or applied AI roles.
• Strong proficiency in Python (NumPy, pandas, scikit-learn, TensorFlow, PyTorch).
• Experience with SQL and data wrangling on large datasets.
• Hands-on experience deploying models into production environments.
• Familiarity with MLOps frameworks and cloud services (Azure ML, AWS Sagemaker, or GCP Vertex AI).
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Experience with NLP, generative AI (LLMs), or computer vision.
• Exposure to data engineering tools (Spark, Databricks, Snowflake).
• Experience in dashboarding/visualization tools (Power BI, Tableau).
• Knowledge of API development and model integration with applications.
• Hybrid work model - candidates based in Virginia (VA) or Texas (TX) preferred.