Data Scientist - Machine Learning

$156,000 - $176,800/Yr

Avispa - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

Professional, Scientific, and Technical Services

About the position

The Data Scientist - Machine Learning role at a leading biotechnology company involves collaborating with multi-disciplinary teams to design, develop, and deploy high-quality data solutions, particularly in Large Language Model (LLM) applications. The position aims to enhance the Product Development organization’s capabilities to meet patient needs through innovative technology. The ideal candidate will contribute to a diverse and friendly team focused on technological advancements and optimal enterprise solutions.

Responsibilities

• Partner with fellow Data Scientists, ML engineers, MLOps/DevOps engineers, and cross-functional teams to solve complex problems using modern NLP technologies, particularly LLMs.
• Build data pipelines and deployment pipelines for ML models.
• Develop ML models according to business and functional requirements.
• Deploy various models and tune them for better performance.
• Document and communicate design and implementation details.
• Contribute to the DSE AI team on technical decisions.
• Collaborate with clients and informatics departments to deploy scalable and easy-to-maintain solutions.
• Serve as a technical point of contact for enterprise-wide technology solutions.
• Lead complex troubleshooting efforts and root cause analysis.

Requirements

• 2+ years of commercial Data Engineering / ML Engineering / MLOps / UI/UX engineering experience.
• 3+ years of commercial software engineering experience.
• Master's degree in a quantitative field (e.g., mathematics, statistics, computer science, EE) or Life Sciences with significant computational experience, or equivalent, with 5+ years working experience in Data Science. PhD is a plus.
• Experience with LLM applications development including tools using and reasoning, such as RAG solutions and code interpreters.
• Experience with LLM fine-tuning is a plus.
• Experience in building data pipelines and deployment pipelines for LLM applications.
• Recent experience with ML/AI toolkits such as AWS Sagemaker; other toolkits like Pytorch, Tensorflow, Keras, MXNet, H2O are nice to have.
• Experience with MLOps technologies (Sagemaker, Vertex AI, Kubeflow).
• Experience with deployment of scalable apps is a plus.
• Experience with clinical study data is a plus.
• Experience with cloud solutions (AWS / Azure / GCP), Docker.
• Proven scripting and automation skills.
• Good knowledge of git, bash, Linux, CI/CD tools (e.g., Jenkins, GitLab CI), software lifecycle, RDB, visualization tools (e.g., Tableau, Jira, Confluence).
• Proficiency in programming languages: Python, R.
• Test-driven development and good coding practices.
• Strong problem-solving and decision-making skills.
• Good interpersonal skills with a customer and delivery focus.
• Ability to work effectively with team members and virtual teams from different locations and cultural backgrounds.

Nice-to-haves

• Experience with LLM fine-tuning.
• Experience with clinical study data.
• Familiarity with additional ML/AI toolkits like Pytorch, Tensorflow, Keras, MXNet, H2O.

Benefits

• Hourly pay: $75-$85/hr (varies based on candidate's experience).
• Group Medical, Dental, Vision, Life insurance.
• Retirement Savings Program.
• Paid Sick Leave (PSL).
• 40 hours/week, 12 Month Assignment.