Principal AI/ML Engineer - VC Backed Startups

Posted Yesterday
Be an Early Applicant
7 Locations
In-Office or Remote
170K-270K Annually
Senior level
Angel or VC Firm • Artificial Intelligence • Information Technology • Software
The Role
Join a talent network connecting Principal AI/ML Engineers with VC-backed startups. Responsibilities include architecting and deploying production ML/DL models, researching state-of-the-art methods (LLMs, transformers, RL), building scalable training/inference pipelines, implementing robust MLOps, optimizing model performance, and leading technical strategy and teams.
Summary Generated by Built In
Join SignalFire’s Talent Network for Principal AI/ML Engineer Roles at VC-Backed Startups

🛑 This is not an application for a specific job. Instead, this is a way to get on the radar of VC-backed startups that are actively hiring AI/ML talent. If you have any questions, please direct inquiries to [email protected].

At SignalFire, we partner with top early-stage startups that are shaping the future of technology. Our portfolio spans 200+ innovative companies across AI, cybersecurity, healthtech, fintech, developer tools, and enterprise SaaS.

We’re looking to connect with exceptional Principal AI/ML Engineers who are excited about driving AI strategy, advancing machine learning research, and scaling AI-powered systems at high-growth startups. By joining SignalFire’s Talent Network, your profile will be shared with our portfolio companies, giving you visibility into exclusive early-stage opportunities that may not be publicly listed.

Who Should Join?

We’re looking for AI/ML experts who are:
✔ Passionate about developing and deploying cutting-edge machine learning and deep learning models
✔ Experienced in architecting scalable AI systems and leading technical teams
✔ Excited to push the boundaries of AI research and apply it to real-world business challenges

Typical Roles & Responsibilities
  • 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, identifying opportunities for innovation and model optimization

  • Develop scalable training and inference pipelines for AI-powered applications

  • Work closely 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

Common Qualifications

While each startup has its own hiring criteria, many Principal AI/ML Engineer roles in our network look for:

  • 8+ years of experience in AI/ML, deep learning, or applied AI

  • Expertise in Python and ML frameworks (TensorFlow, PyTorch, JAX, 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 (Apache Spark, Kafka, Hadoop) and MLOps platforms (MLflow, TFX, SageMaker)

  • Deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines

  • Experience with model quantization, fine-tuning, and optimization for performance

  • Strong knowledge of cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)

  • A track record of technical leadership, mentoring, and driving AI innovation

💡 Technologies You Might Work With:
  • Languages & Frameworks: Python, TensorFlow, PyTorch, JAX, Hugging Face Transformers

  • MLOps & Data Pipelines: MLflow, Kubeflow, TFX, Apache Spark, Airflow, Ray

  • Cloud & Deployment: AWS SageMaker, GCP Vertex AI, Azure ML, Kubernetes, Docker

  • Big Data & Storage: Apache Kafka, Hadoop, BigQuery, Snowflake, Redis, NoSQL databases

  • Model Optimization: ONNX, TensorRT, pruning, quantization, distillation

What Happens Next?
  1. Submit your application to join SignalFire’s Talent Ecosystem.

  2. We review applications on an ongoing basis to identify strong candidates.

  3. If there’s a match, a SignalFire talent partner or a leader from one of our startups may reach out directly.

  4. No match yet? We’ll keep your profile on file for future AI/ML roles in our portfolio.

Skills Required

  • 8+ years of experience in AI/ML, deep learning, or applied AI
  • Expertise in Python and ML frameworks (TensorFlow, PyTorch, JAX, 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 (Apache Spark, Kafka, Hadoop) and MLOps platforms (MLflow, TFX, SageMaker)
  • Deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines
  • Experience with model quantization, fine-tuning, and optimization for performance
  • Strong knowledge of cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)
  • Track record of technical leadership, mentoring, and driving AI innovation

SignalFire Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about SignalFire and has not been reviewed or approved by SignalFire.

  • Healthcare Strength Benefit details indicate employer-paid comprehensive medical, dental, vision, and long-term disability for employees and dependents. Feedback suggests this level of coverage is a standout strength for a small venture firm.
  • Leave & Time Off Breadth Policy language highlights unlimited or flexible paid time off across job postings. Feedback suggests this supports work-life balance when paired with collaborative norms.
  • Parental & Family Support Listings include dedicated fertility benefits in certain roles. Feedback suggests targeted family-building support enhances the overall package for those prioritizing these benefits.

SignalFire Insights

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The Company
HQ: San Francisco, CA
97 Employees
Year Founded: 2012

What We Do

SignalFire is the first venture capital firm built like a technology company to better solve for the needs of founders. The core of its value-add is Beacon, the AI engine SignalFire has been refining since the firm's launch in 2013. Beacon tracks more than 600 million employees and 80 million companies to guide the fund’s investing and assist portfolio companies with scaling their teams and revenue. SignalFire also helps early-stage founders navigate the toughest parts of building a company at every stage, with expert advisors, 100 skill-building workshops a year, and an in-house team of recruiters, data scientists, PR experts, and go-to-market leaders. With over $2.1 billion in assets under management, SignalFire focuses on investing from seed to scale. The firm’s key sectors include AI/ML, developer tools, B2B SaaS, healthcare, cybersecurity, and consumer. https://www.signalfire.com/disclosures

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