Principal AI/ML Engineer

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SignalFire

11 - 50 employees

Founded 2012

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

SignalFire is a venture capital firm built on technology and data, dedicated to supporting growth for early-stage companies through advanced AI tools and seasoned sector expertise. They focus on providing unparalleled support to their portfolio companies, combining in-house AI capabilities with tailored advisory programs across multiple sectors such as healthcare, fintech, cybersecurity, and more.

📋 Description

• Join SignalFire’s Talent Network for Principal AI/ML Engineer roles at VC-backed startups rather than applying for one specific job • Architect, develop, and optimize machine learning and deep learning models for production systems • Research and apply state-of-the-art AI methodologies, including LLMs, transformers, and reinforcement learning • Lead AI strategy and identify opportunities for innovation and model optimization • Develop scalable training and inference pipelines for AI-powered applications • Work with engineering, data, and product teams to integrate AI/ML into business solutions • Optimize ML models for efficiency, accuracy, and scalability in real-world deployments • Ensure robust MLOps practices, including model monitoring, retraining, and deployment automation • Collaborate on AI/ML research publications, patents, and open-source contributions • SignalFire reviews applications on an ongoing basis and may connect matched candidates with portfolio-company talent partners or leaders

🎯 Requirements

• 8+ years of experience in AI/ML, deep learning, or applied AI • Expertise in Python and ML frameworks including TensorFlow, PyTorch, JAX, and Hugging Face Transformers • Strong background in computer vision, NLP, generative AI, or reinforcement learning • Experience developing scalable AI pipelines, data processing workflows, and distributed training systems • Familiarity with big data tools including Apache Spark, Kafka, and Hadoop • Familiarity with MLOps platforms including MLflow, TFX, and SageMaker • Deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines • Experience with model quantization, fine-tuning, and performance optimization • Strong knowledge of AWS, GCP, Azure, Docker, and Kubernetes • Track record of technical leadership, mentoring, and driving AI innovation • Required application materials include full name, email, LinkedIn URL, resume/CV, and current or preferred working location

🏖️ Benefits

• Equity offered • Profile visibility into exclusive early-stage opportunities • Potential consideration for future AI/ML roles across SignalFire’s portfolio • Opportunity to receive occasional newsletters, insights, or invitations to community events (with opt-out) • Ability to request updates or removal of personal information from SignalFire records

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