Senior ML/AI Engineer

We're the #1 TikTok Shop partner helping brands like Under Armour, Hanes, HeyDude, and Logitech scale their affiliate marketing. We've crossed 7 figures in ARR, and are rapidly scaling our team this year. Our vision is to become the Hubspot for creator marketing, powering brands and creators to connect and grow across all commerce platforms (Youtube Shopping, Instagram Shopping, Shopify, Amazon).

We're building key infrastructure for the creator economy and implementing AI with the world's largest brands and creators. Your work will directly impact users on day 1—our user base depends on our product daily.

Your work will directly impact users on day 1. We have a highly responsive user base that depends on our product day in and day out.

• Own ML systems end-to-end: research, prototype, train, deploy, and iterate rapidly

• Build multimodal ML systems for video, text, images, and audio at scale

• Design and deploy LLM-powered applications using RAG and AI APIs

• Develop content understanding and classification models for text and visual data

• Build search and discovery systems using embeddings and semantic retrieval

• Create audio analysis and processing pipelines

• Build MLOps infrastructure—data pipelines, model serving, monitoring, and experiment tracking

• Ideate ML/AI product features with product and customers

• Leverage modern AI tools to accelerate development

• Work directly with customers and translate vague requirements into shipped ML solutions

• Ship fast and learn fast—high urgency environment
  

• You have 4–8 years of ML engineering experience building and deploying models in production

• You have strong Python and ML fundamentals and write clean, maintainable production code

• You've built ML models end-to-end: data pipelines, training, serving, monitoring

• You're experienced with modern ML frameworks (PyTorch, TensorFlow, scikit-learn)

• You have production experience with LLMs and AI APIs (OpenAI, Anthropic, Hugging Face)

• You can build ML systems across multiple domains—NLP, computer vision, and audio

• You're product-minded and identify where ML can solve user problems and improve business metrics

• You're comfortable with MLOps tools and cloud platforms (AWS or GCP)

• You're resourceful and thrive in ambiguous environments
  

• Core ML: Supervised/unsupervised learning, feature engineering, model evaluation, A/B testing

• Deep Learning: Neural networks, transformers, CNNs, training and optimization

• NLP/LLMs: RAG systems, prompt engineering, vector databases, fine-tuning, LangChain

• Computer Vision: Image classification, object detection, OCR, visual content understanding, image embeddings

• Audio/Speech: Audio classification, speech recognition (ASR), audio transcription

• Search & Retrieval: Semantic search, embedding models, vector similarity, multimodal retrieval

• MLOps: Model serving, monitoring, experiment tracking (MLflow, Weights & Biases), data pipelines

• Cloud ML: AWS (SageMaker, Bedrock) or GCP (Vertex AI), model deployment, scalable inference
  

• You've worked at an early-stage startup or been a first/early ML hire

• You have experience building multimodal search systems or semantic retrieval at scale

• You have experience with video understanding—extracting features, generating embeddings, or analyzing visual content

• You've implemented feature stores or advanced MLOps infrastructure

• You have experience with real-time inference and low-latency model serving

• You have expertise in adversarial robustness and model safety testing

• You've built hybrid RAG + fine-tuning systems

• You have experience with multimodal models (vision + language, audio + text)

• You're experienced with model optimization (quantization, distillation, pruning)

• You have a track record of shipping ML-driven product features that moved key metrics

• You've shipped side projects or contributed to open-source ML projects
  

• Post-revenue company solving real problems for real customers

• Be the ML/AI leader—define our ML strategy and infrastructure as we scale

• High autonomy and visibility—no boring tickets

• Your models reach users within days, not months

• Strong engineering-first culture

• Shape both the product and the company

• Work on diverse ML problems across video, language, and audio

• Direct impact on product strategy—your ML ideas become features
  

Feel free to send a short note about something you've built and why this role excites you. GitHub/LinkedIn/resume is great, but we care more about how you think and build!