Remote Principal AI/ML Engineer - VC Backed Startups

Description:

• SignalFire is seeking exceptional Principal AI/ML Engineers to connect with top early-stage startups shaping the future of technology.
• The role involves driving AI strategy, advancing machine learning research, and scaling AI-powered systems at high-growth startups.
• By joining SignalFire’s Talent Network, candidates will gain visibility into exclusive early-stage opportunities that may not be publicly listed.
• This is not an application for a specific job but a way to get on the radar of VC-backed startups actively hiring AI/ML leaders.
• Candidates will be responsible for architecting, developing, and optimizing machine learning and deep learning models for production systems.
• They will research and apply state-of-the-art AI methodologies, including LLMs, transformers, and reinforcement learning.
• The role includes leading AI strategy, identifying opportunities for innovation and model optimization, and developing scalable training and inference pipelines for AI applications.
• Collaboration with engineering, data, and product teams is essential to integrate AI/ML into business solutions.
• Candidates will optimize ML models for efficiency, accuracy, and scalability in real-world deployments and ensure robust MLOps practices.
• They will also collaborate on AI/ML research publications, patents, and open-source contributions.

Requirements:

• Candidates should have 8+ years of experience in AI/ML, deep learning, or applied AI.
• Expertise in Python and ML frameworks such as TensorFlow, PyTorch, JAX, and Hugging Face Transformers is required.
• A strong background in computer vision, NLP, generative AI, or reinforcement learning is essential.
• Experience in developing scalable AI pipelines, data processing workflows, and distributed training systems is necessary.
• Familiarity with big data tools like Apache Spark, Kafka, and Hadoop, as well as MLOps platforms such as MLflow, TFX, and SageMaker, is expected.
• A deep understanding of LLMs, transformer architectures, and retrieval-augmented generation (RAG) pipelines is required.
• Candidates should have experience with model quantization, fine-tuning, and optimization for performance.
• Strong knowledge of cloud environments (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) is necessary.
• A track record of technical leadership, mentoring, and driving AI innovation is essential.

Benefits:

• Joining SignalFire’s Talent Network provides access to exclusive early-stage opportunities at innovative startups.
• Candidates will have the chance to work on cutting-edge AI technologies and methodologies.
• The role offers the opportunity to collaborate with top talent in the AI/ML field and contribute to impactful projects.
• Successful candidates may receive direct outreach from startups interested in their background and expertise.
• SignalFire will keep candidate profiles on file for future AI/ML roles in their portfolio, ensuring ongoing opportunities.