Highlight AI is looking to solve the problem of user productivity by creating a desktop assistant that integrates with workflows, allowing users to interact with applications using text and voice commands, thus eliminating the need to switch between tools. The company is in a hypergrowth phase and needs to expand its team to drive the design, development, and deployment of advanced ML models and systems that power its core product features.
Requirements
- Solid understanding of ML fundamentals: supervised & unsupervised learning, deep learning, model evaluation metrics, deployment, inference latency trade-offs
- Familiarity with knowledge representation and retrieval: building or leveraging knowledge graphs, embeddings, and memory systems to support contextual inference and long-term model learning
- Experience deploying models at scale in production (AWS/GCP/Azure)
- Experience with data engineering (ETL pipelines, feature stores, large datasets) and production-grade MLOps (CI/CD, monitoring, retraining workflows)
- Published research or open-source contributions
- Experience with genAI (LLMs, diffusion models), computer vision, multimodal ML
- Knowledge of prompt engineering, RAG, embeddings
Responsibilities
- Design and implement knowledge graph or memory systems to enable contextual retrieval, reasoning, and persistent knowledge for the core Highlight application
- Research, prototype and deploy state-of-the-art machine learning text and OCR models (e.g., transformer architectures, computer vision, time series forecasting, reinforcement learning)
- Build pipelines for data ingestion, feature engineering, model training, evaluation, and deployment
- Work on productionizing models: monitoring, scalability, latency, retraining, A/B testing, and model lifecycle management
- Develop infrastructure and tooling to support ML experimentation and production (e.g., model serving, MLOps, observability)
- Collaborate with cross-functional partners (product managers, software engineers, UX researchers) to integrate ML features into product flows
- Keep abreast of latest ML/AI research, propose novel approaches, publish (internally or externally) when appropriate
Other
- This is an on-site role, requiring five days a week in our NYC headquarters.
- Ownership mentality (no task is too small for you) – it’s all hands on deck here and we need everyone rowing the boat.
- Deep understanding of system architecture and design patterns – we’re looking for someone who can hit the ground running day one.
- Excellent communication skills and a collaborative mindset – we’re extremely lean so we’re looking for a team player who works well with others.
- Must be based in or willing to relocate to NYC – although we’re flexible with days off & schedules, we have a 100% in-office culture during the week.
