Job description

Join SignalFire's Talent Network for Founding AI Engineer Roles at VC-Backed Startups 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. 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 talentnetwork@signalfire.com. 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.

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