Principal AI/ML Engineer

SignalFire

Principal AI/ML Engineer architecting scalable models, pipelines, and MLOps for SignalFire’s VC-backed startup portfolio. Driving AI research, strategy, optimization, and production deployment across high-growth companies.

Posted 8/5/2026full-time🇺🇸 United StatesLead💰 $170,000 - $270,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and optimizing machine learning and deep learning models, with a strong focus on developing scalable AI pipelines and implementing robust MLOps practices. Proven ability to lead AI strategy and collaborate effectively with cross-functional teams to drive innovation.

Highest-signal resume keywords

Machine Learning Model OptimizationPython ProgrammingTensorFlow FrameworkMLOps PracticesCloud Environments (AWS, GCP, Azure)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningComputer VisionNatural Language ProcessingReinforcement LearningModel QuantizationPerformance OptimizationData Processing WorkflowsDistributed Training SystemsAI Methodologies

Soft Skills

Technical LeadershipMentoringCollaboration

Tools & Technologies

Apache SparkKafkaHadoopMLflowTFXSageMakerDockerKubernetesHugging Face TransformersJAX

Industry Keywords

AI StrategyInnovationModel MonitoringRetrainingDeployment AutomationOpen-Source ContributionsResearch PublicationsRetrieval-Augmented Generation

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDockerGoogle Cloud PlatformHadoopKafkaKubernetesPythonPyTorchSparkTensorflow

About the role

Key responsibilities & impact

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 by 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
Submit an application to join SignalFire’s Talent Ecosystem
SignalFire reviews applications on an ongoing basis and may connect matched candidates with portfolio-company talent partners or leaders

Requirements

What you’ll need

8+ years of experience in AI/ML, deep learning, or applied AI
Expertise in Python and ML frameworks including TensorFlow, PyTorch, JAX, and 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 including Apache Spark, Kafka, and Hadoop
Familiarity with MLOps platforms including MLflow, TFX, and SageMaker
Deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines
Experience with model quantization, fine-tuning, and performance optimization
Strong knowledge of cloud environments including AWS, GCP, and Azure
Experience with containerization tools including Docker and Kubernetes
Track record of technical leadership, mentoring, and driving AI innovation
Required application materials: full name, email, LinkedIn URL, resume/CV, and current or preferred working location

Benefits

Comp & perks

$170K – $270K base compensation
Offers Equity
Potential access to exclusive early-stage opportunities through SignalFire’s portfolio
Profile kept on file for future AI/ML roles in SignalFire’s portfolio
Occasional communications such as newsletters, insights, or invitations to community events (opt-in)