Description:

SignalFire is seeking exceptional Founding AI Engineers to join high-growth startups as core technical leaders.
This opportunity allows candidates to connect with top early-stage startups shaping the future of technology.
By joining SignalFire’s Talent Network, candidates will gain visibility into exclusive early-stage opportunities that may not be publicly listed.
Candidates will be responsible for designing, developing, and deploying machine learning (ML) and deep learning models.
They will build scalable data pipelines for preprocessing, feature engineering, and model training.
The role involves optimizing and deploying AI models for real-time and batch processing.
Candidates will work closely with founders to align AI strategies with product and business goals.
They will research and integrate state-of-the-art AI methodologies and develop and optimize RAG pipelines, agent architectures, and LLM-powered systems.

Requirements:

Candidates should have 3+ years of experience in machine learning, deep learning, or applied AI.
Strong Python skills with frameworks like TensorFlow, PyTorch, or JAX are required.
Experience with big data tools such as Apache Spark, Kafka, or Hadoop and MLOps platforms is necessary.
Familiarity with cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) is essential.
Startup experience or an interest in early-stage environments is a plus.

Joining SignalFire’s Talent Network provides access to exclusive early-stage opportunities in VC-backed startups.
Candidates will have the chance to work directly with founders and shape AI strategy in innovative environments.
The network allows for ongoing review of applications to identify strong candidates for future roles.
If a match is found, candidates may be contacted directly by a SignalFire talent partner or a leader from one of the startups.