SignalFire
Principal AI/ML Engineer – VC Backed Startups
Posted 2 days ago. Be among the first 25 applicants.
This range is provided by SignalFire. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $170,000 – $270,000 per year
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
talentnetwork@signalfire.com .
Who Should Join?
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
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: $170,000 – $270,000 per year
#J-18808-Ljbffr
This range is provided by SignalFire. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $170,000 – $270,000 per year
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
talentnetwork@signalfire.com .
Who Should Join?
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
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: $170,000 – $270,000 per year
#J-18808-Ljbffr