Signify Technology
Artificial Intelligence Engineer
Signify Technology, San Francisco, California, United States, 94199
This range is provided by Signify Technology. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range
$200,000.00/yr - $300,000.00/yr Title: Generative AI Backend Software Engineer Location: San Fransisco (5 days onsite) Base Salary Range: $200,000-$300,000 About the Role
A growing venture-backed biotech/AI company is developing AI-driven solutions to accelerate drug discovery by addressing one of the most pressing challenges in the field: predicting safety and toxicity. Toxicity is responsible for a large percentage of failed drug programs, and solving this problem can dramatically reduce time-to-market for new medicines. The engineering team is looking for backend and distributed systems engineers who want to build the data pipelines, infrastructure, and platforms that transform raw chemical, biological, and clinical information into machine learning–ready datasets and actionable insights. This work directly supports internal research teams and external customers by enabling large-scale inference, LLM-powered literature research, and robust data platforms. This opportunity is ideal for engineers who are motivated by building clean, reliable systems that have direct, real-world impact, and who want to operate at the intersection of AI, engineering, and the life sciences. Responsibilities
Design and build the core infrastructure behind large-scale ML systems, including data pipelines, model serving, and customer-facing platforms. Architect scalable systems for inference, storage, and retrieval of diverse scientific datasets. Deploy advanced reasoning agents and ML models from research into production environments. Work closely with researchers in AI, chemistry, and biology, helping translate scientific workflows into reliable engineering systems. Contribute to building a strong engineering culture that emphasizes quality, reliability, and impact. Requirements
Strong generalist software engineering background with expertise in backend, cloud, and distributed systems. Experience designing and scaling infrastructure for enterprise ML systems, including training, inference, and monitoring. Familiarity with handling complex datasets and automating ETL workflows. Hands-on experience deploying SaaS products or enterprise-grade software. Curiosity to learn across domains—AI, scientific research, and product development. Strong ownership mindset, with a focus on reliability and customer impact. Why This Role is Unique
This team is tackling a challenge that sits at the center of both AI and drug discovery, building technology that could reshape how new medicines are developed. The role offers the opportunity to contribute directly to solving high-impact problems while working in a fast-paced, venture-backed startup environment with clear pathways for growth and ownership. Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Science and Research Industries: Biotechnology Research and Software Development
#J-18808-Ljbffr
$200,000.00/yr - $300,000.00/yr Title: Generative AI Backend Software Engineer Location: San Fransisco (5 days onsite) Base Salary Range: $200,000-$300,000 About the Role
A growing venture-backed biotech/AI company is developing AI-driven solutions to accelerate drug discovery by addressing one of the most pressing challenges in the field: predicting safety and toxicity. Toxicity is responsible for a large percentage of failed drug programs, and solving this problem can dramatically reduce time-to-market for new medicines. The engineering team is looking for backend and distributed systems engineers who want to build the data pipelines, infrastructure, and platforms that transform raw chemical, biological, and clinical information into machine learning–ready datasets and actionable insights. This work directly supports internal research teams and external customers by enabling large-scale inference, LLM-powered literature research, and robust data platforms. This opportunity is ideal for engineers who are motivated by building clean, reliable systems that have direct, real-world impact, and who want to operate at the intersection of AI, engineering, and the life sciences. Responsibilities
Design and build the core infrastructure behind large-scale ML systems, including data pipelines, model serving, and customer-facing platforms. Architect scalable systems for inference, storage, and retrieval of diverse scientific datasets. Deploy advanced reasoning agents and ML models from research into production environments. Work closely with researchers in AI, chemistry, and biology, helping translate scientific workflows into reliable engineering systems. Contribute to building a strong engineering culture that emphasizes quality, reliability, and impact. Requirements
Strong generalist software engineering background with expertise in backend, cloud, and distributed systems. Experience designing and scaling infrastructure for enterprise ML systems, including training, inference, and monitoring. Familiarity with handling complex datasets and automating ETL workflows. Hands-on experience deploying SaaS products or enterprise-grade software. Curiosity to learn across domains—AI, scientific research, and product development. Strong ownership mindset, with a focus on reliability and customer impact. Why This Role is Unique
This team is tackling a challenge that sits at the center of both AI and drug discovery, building technology that could reshape how new medicines are developed. The role offers the opportunity to contribute directly to solving high-impact problems while working in a fast-paced, venture-backed startup environment with clear pathways for growth and ownership. Details
Seniority level: Mid-Senior level Employment type: Full-time Job function: Science and Research Industries: Biotechnology Research and Software Development
#J-18808-Ljbffr