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.
💡 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/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
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
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
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
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.
