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 Staff AI and Machine Learning engineers who are excited about joining high-growth startups as founding or early team members. 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.
💡 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].
Who Should Join?We’re looking for AI engineers who are:
✔ Building cutting-edge AI/ML models and deploying them in production
✔ Excited about joining early-stage startups in transformative industries
✔ Interested in staying connected with SignalFire’s portfolio for future opportunities
Typical roles and responsibilities may include:
Developing and deploying machine learning (ML) and deep learning models
Building scalable data pipelines for training and inference
Working directly with founders to align AI strategies with product roadmaps
Researching and implementing state-of-the-art AI methodologies
Optimizing RAG pipelines, agent architectures, and LLM-powered systems
While each startup has its own hiring criteria, many AI engineering roles in our network look for:
6+ years of experience in AI/ML, 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, Kubernetes, Docker, MLflow, Kubeflow, FastAPI, SQL, NoSQL, Airflow, Spark, Kafka, Hadoop, 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.
Top Skills
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
