Senior Machine Learning Engineer / Researcher (NYC)

Highlight AI•New York, NY

85d•Onsite

About The Position

Highlight AI is a cutting-edge desktop assistant designed to enhance productivity by seamlessly integrating with your workflow. We empower users to interact with any application using text and voice commands, eliminating the need to switch between tools. After raising a seed round from investors like Khosla Ventures, Sapphire Ventures, General Catalyst, Valor Equity, SV Angel, and Conviction Fund, we’re now in hypergrowth mode and expanding our team. As a Senior Machine Learning Engineer, you will drive the design, development, and deployment of advanced ML models and systems that power our core product features. You will collaborate closely with product, engineering, and data teams to translate research into production-ready services, while also advancing our longer-term R&D roadmap. This is a highly technical role for someone who’s excited to work at the intersection of desktop software, native development, and AI integration, and who thrives in a fast-paced, collaborative environment. Note: this is an on-site role, requiring five days a week in our NYC headquarters.

Requirements

A Master’s or PhD in Computer Science, Machine Learning, Statistics, Applied Math or equivalent experience.
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
5+ years of hands-on experience building machine learning models in production environments – we ship features fast, so we need someone who can keep up.
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)
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.

Nice To Haves

Published research or open-source contributions
Experience with genAI (LLMs, diffusion models), computer vision, multimodal ML
Knowledge of prompt engineering, RAG, embeddings
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.
Type-A tendencies: maybe you’re extremely detail-oriented. Or maybe you take pride in shipping high-quality products. Whatever it is you do, you give it your all.

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
Participate in architecture discussions & technical direction for ML/AI at the company