Machine Learning Engineer
3 weeks ago
Job Title: Machine Learning Engineer
About PromptBio:
We're a leading biotechnology company based in Pleasanton, California, dedicated to leveraging AI-driven workflows for discovering novel biomarkers from multi-omics data. Our goal is to translate these findings into clinical diagnostic applications.
Key Responsibilities:
- Design and implement automated computational workflows for analyzing complex multi-omics data.
- Develop and apply machine learning methods to identify novel biomarkers, addressing existing gaps in analytical tools.
- Collaborate with our business development team to present technical solutions to clients and create case studies showcasing our platform's capabilities.
- Work closely with bioinformatics and software engineering teams to deploy robust, production-quality software solutions.
Estimated Salary: $100,000 - $160,000 per year
Requirements:
- Proven experience with large language models (LLMs) and generative AI technologies.
- Hands-on experience with agentic automation frameworks (e.g., LangChain, DSPy, CrewAI).
- Minimum of 2 years in developing machine learning applications.
- Proficiency in programming languages such as Python or Go, with adaptability to learn new languages as needed.
- Familiarity with software engineering best practices, including testing, code reviews, version control (e.g., Git), and containerization.
- Experience with cloud computing environments (AWS, GCP) and Linux servers is advantageous.
- Knowledge of multi-omics data analysis and next-generation sequencing (NGS) is a significant plus.
- Master's or Ph.D. in Machine Learning, AI, Computer Science, Statistics, or a related field.
Benefits:
- Competitive compensation package, including incentives and retirement plan.
- Healthcare and well-being programs, including medical, dental, vision benefits, and more.
- Generous paid time-off, including vacation, sick time, holidays, and discretionary winter shutdown.
- 401(k) retirement savings with a generous company match.
- Hybrid work opportunities.
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