Role overview
📍 Hybrid – New York City (open to remote U.S. candidates within commutable distance to NYC)
Overview
We are hiring on behalf of a client seeking talented
AI/ML Engineers
to join their growing team. This is a unique opportunity to shape the future of
AI-powered products
by developing, prototyping, and deploying innovative machine learning and generative AI systems at scale. You’ll work across the full spectrum of applied AI, from data science and model development to large-scale engineering and production deployment.
What you'll work on
- Prototype and Deploy AI Solutions
- Rapidly prototype, iterate, and ship AI-powered experiences using the latest capabilities of LLMs, agent frameworks, and recommender systems.
- Architect and deploy ML/GenAI products on cloud platforms (AWS, GCP, or similar).
- Build and maintain end-to-end AI workflows including data ingestion, feature engineering, modeling, evaluation, and deployment.
- AI Engineering & Orchestration
- Design and manage ML orchestration frameworks (Airflow, Kedro, ZenML, Flyte, etc.) to ensure scalability and reproducibility.
- Integrate LLMs and data into autonomous, multi-step workflows.
- Critically review AI-generated code for correctness, performance, and engineering best practices.
- Cross-Functional Collaboration
- Partner with product, design, research, and data science teams to take ideas from concept to launch.
- Translate complex business problems into AI-driven solutions with measurable impact.
- Innovation & Best Practices
- Stay on top of cutting-edge AI research and open-source innovation, incorporating new tools and techniques into production.
- Promote responsible, ethical, and impactful AI practices.
- Share thought leadership and help build a strong engineering culture in applied AI.
What we're looking for
- Prior experience launching AI/ML products into production.
- Exposure to graph-based models, multi-agent AI systems, and generative models (LLMs, diffusion, etc.).
- Experience with data-driven decision making, A/B testing, and advanced evaluation strategies .
- Familiarity with AI coding assistants and rapid prototyping tools.
- Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc.
- Build features end-to-end using technologies like TypeScript, MongoDB, and Elasticsearch, and contribute to our compute orchestration layer powered by Temporal.
- Technical skills including familiarity with Python, GPU, AWS, API, LLM, ML, and SQL
- Experience across the stack: React, Typescript, Node, Python, etc.