Signalfire LLC
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?
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.
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?
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.