Principal AI/ML Engineer

SignalFire

Principal AI/ML Engineer advancing machine learning strategy and production systems for SignalFire’s VC-backed startup portfolio. Researching LLMs, scalable pipelines, MLOps, and model optimization.

Posted 8/5/2026full-timeNew York City • New York • 🇺🇸 United StatesLead💰 $170,000 - $270,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

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 OptimizationDeep Learning ExpertisePython ProgrammingMLOps PracticesAI Strategy Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningComputer VisionNatural Language ProcessingGenerative AIReinforcement LearningModel QuantizationPerformance OptimizationData Processing WorkflowsDistributed Training Systems

Soft Skills

Technical LeadershipMentoringCollaboration

Tools & Technologies

TensorFlowPyTorchJAXHugging Face TransformersApache SparkKafkaHadoopMLflowTFXSageMaker

Industry Keywords

AI MethodologiesLLMsTransformersRetrieval-Augmented GenerationCloud PlatformsAWSGCPAzureDockerKubernetes

Tech Stack

Tools & technologies

ApacheAWSAzureDockerGoogle 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; if matched, engage with SignalFire talent partners or portfolio-company 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 AWS, GCP, Azure, Docker, and Kubernetes
Track record of technical leadership, mentoring, and driving AI innovation
LinkedIn URL and resume/CV required for the Talent Network submission

Benefits

Comp & perks

Equity offered
Potential access to exclusive early-stage opportunities through SignalFire’s Talent Network
Profile shared with SignalFire portfolio companies for future opportunity matching