SignalFire
AI

Principal AI/ML Engineer - VC Backed Startups

SignalFire · · $170k - $270k

Actively hiring Posted 7 months ago

Join SignalFire’s Talent Network for Principal AI/ML 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 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
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?

  • 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.

Compensation Range: $170K - $270K

Tags & focus areas

Used for matching and alerts on DevFound
Fulltime Ai Machine Learning Deep Learning Computer Vision Mlops Generative Ai Pytorch Tensorflow Ai Engineer
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.