Lead Data Scientist/Machine Learning Engineer

GSPANN - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

1,001-5,000 employees

Professional, Scientific, and Technical Services

About the position

The Lead Data Scientist/Machine Learning Engineer at GSPANN is responsible for leveraging expertise in machine learning and data science to deliver innovative solutions for clients. This role involves working closely with business stakeholders to optimize IT capabilities and practices, while also leading projects that utilize advanced technologies in natural language processing and machine learning. The position requires a strong technical background and the ability to work both independently and collaboratively in a team environment.

Responsibilities

• Lead the development and implementation of machine learning models and algorithms.
• Collaborate with business stakeholders to understand their needs and translate them into technical requirements.
• Utilize natural language processing techniques to enhance data analysis and model performance.
• Ensure adherence to software best practices, including version control, CI/CD, and documentation.
• Conduct prompt engineering and fine-tuning of large language models (LLMs).
• Participate in DevOps/MLOps processes to streamline model deployment and monitoring.
• Communicate findings and insights effectively to both technical and non-technical audiences.

Requirements

• 5+ years of experience in software engineering, machine learning, data science, or artificial intelligence.
• Strong proficiency in Python/Pyspark.
• Experience with software best practices in team settings, including version control (Git), CI/CD, documentation, and unit testing.
• Familiarity with NLP and/or ML Python frameworks such as PyTorch, TensorFlow, Transformers/Hugging Face, and NumPy.
• Strong background in natural language processing, machine learning, and deep learning.
• Hands-on experience with LLM skills including prompt engineering, fine-tuning, LLMOps, function-calling, and retrieval augmented generation (RAG).
• Exposure to Microsoft Azure or similar cloud computing ecosystem is preferred.
• Experience with DevOps/MLOps/LLMOps is strongly preferred.
• Excellent written and verbal communication and presentation skills.

Nice-to-haves

• Experience in a consulting environment.
• Familiarity with agile methodologies.

Benefits

• Competitive benefits package.
• Educational assistance.
• Career growth opportunities.