Job Details

Lead Stack Inc. is an award-winning, one of the nation's fastest-growing, certified minority-owned (MBE) staffing services provider of contingent workforce. As a recognized industry leader in contingent workforce solutions and Certified as a Great Place to Work, we're proud to partner with some of the most admired Fortune 500 brands in the world.

TITLE: Data Scientist
LOCATION: San Francisco Metro – Remote
DURATION: 9+ Months
Rate $100 - $120/hr

Job Description:
We are looking for talented AI Software Engineers to join our team and build a cutting-edge AI platform for Enterprise IAM Security. The ideal candidate will have a strong foundation in machine learning, deep learning, and software engineering. You'll work on state-of-the-art AI models, optimize infrastructure for scalability, and collaborate with cross-functional teams to deliver innovative solutions.

Responsibilities:

• Analyze large datasets to identify trends, opportunities, and challenges in the tools and AI-powered features.
• Build datasets for testing models, both generative and predictive, in collaboration with partner teams.
• Participate in technical discussions, and drive engineering investments in responsible AI to improve model fairness and safety prior to launch.
• Compare between different tools and libraries options (both Client built and open-source) to identify the most appropriate one for the task at hand.
• Develop quantitative metrics to help surface insights from structured datasets.
• Develop and maintain reports and dashboards to track key metrics and KPIs.
• Monitor and analyze logs data for harms/ threats and insights.
• Create data visualizations to communicate insights and trends to stakeholders.
• Ensure data quality and integrity by identifying and addressing data discrepancies and errors.

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Fluent in building/prototyping machine learning models and algorithms and wrangling large datasets.
• At least 5+ years of hands-on experience in engineering positions passionate about Machine Learning, Information Retrieval, Recommendation systems, Personalization (p13n), Natural Language Processing, Learning to Rank, RAG.
• Proficient in using Python and common machine learning frameworks (e.g., TensorFlow, Pandas, PyTorch, SciPy, scikit-learn, JAX) to implement models and algorithms.
• Experience deploying and managing AI solutions on cloud platforms such as AWS SageMaker and Amazon Bedrock.
• Proficient in SQL, shell scripting, and Unix/Linux command-line tools.
• Grasp of the evolving understanding of fairness and ability to meet both state-of-the-art and global standards for fairness evaluation, particularly in generative AI.
• Experience working across teams of engineers, data scientists, and researchers.

• Experience with designing and building micro-services, familiar with Kubernetes/Terraform/Docker/RESTful API/gRPC, etc.
• Experience with Agile software development and Test Driven Development methodologies.