Founding AI Engineer (Senior/Staff) - VC Backed Startups

Join SignalFire’s Talent Network for Founding AI 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 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 Founding AI Engineers who are excited about joining high-growth startups as core technical leaders. 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 engineers who are:

Passionate about building AI/ML models from the ground up and deploying them in production

Excited about joining early-stage startups and working directly with founders

Interested in shaping AI strategy and leading the development of AI-powered products

Typical Roles & Responsibilities

• Designing, developing, and deploying machine learning (ML) and deep learning models

• Building scalable data pipelines for preprocessing, feature engineering, and model training

• Optimizing and deploying AI models for real-time and batch processing

• Working closely with founders to align AI strategies with product and business goals

• Researching and integrating state-of-the-art AI methodologies

• Developing and optimizing RAG pipelines, agent architectures, and LLM-powered systems

Common Qualifications

While each startup has its own hiring criteria, many founding AI roles in our network look for:

• 3+ years of experience in machine learning, deep learning, or applied AI

• Strong Python skills with frameworks like TensorFlow, PyTorch, or JAX

• Experience with big data tools (Apache Spark, Kafka, Hadoop) and MLOps platforms

• Familiarity with cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes)

• Startup experience or an interest in early-stage environments is a plus

Technologies You Might Work With: Python, TensorFlow, PyTorch, JAX, scikit-learn, Kubernetes, Docker, MLflow, TFX, Kubeflow, FastAPI, Flask, SQL, NoSQL, Apache Spark, Kafka, Hadoop, Flink, Airflow, AWS (SageMaker, Lambda, S3), GCP (Vertex AI, BigQuery), Azure (ML Studio, Synapse).

What Happens Next?

• Submit your application to join SignalFire’s Talent Ecosystem.

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

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

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