Member of Technical Staff
Listed on 2026-01-01
-
IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Location: New York
Overview
We are an industry-leading startup developing AI for consumer brands. Our solutions leverage machine learning, generative AI, agent-based systems, and graph technologies to give our customers insights in seconds and business impact in minutes using our products.
RoleAs a Founding Member of Technical Staff (Contract to Hire), you will work in a hybrid capacity as both a Data Scientist and Machine Learning Engineer, playing a pivotal role in designing, building, and deploying the intelligence behind our AI products. You’ll work across the full spectrum of applied AI—spanning data science, machine learning, and large‑scale production engineering. This hybrid role requires both deep expertise in developing innovative models and the engineering discipline to deploy and maintain them in robust, scalable systems.
You’ll collaborate closely with data engineers, product leads, backend engineers, and customer‑facing teams to ensure that our AI systems deliver measurable value in real‑world environments. As one of the earliest technical hires, you will help define our AI strategy, set technical standards, and establish best practices for applied AI at scale.
- Architect, build, and deploy ML/GenAI products on cloud infrastructure (AWS or similar).
- Design and implement end‑to‑end AI workflows: data ingestion, feature engineering, modeling, evaluation, and deployment.
- Create automated pipelines for continuous learning, model promotion, and performance monitoring.
- Lead the design of ML orchestration frameworks (Airflow, Kedro, ZenML, Flyte) to ensure reproducibility and scalability.
- Oversee deployment of large‑scale and multi‑agent AI systems with high reliability and fault tolerance.
- Continuously optimize workflows for efficiency, robustness, and performance in production.
- Translate complex business problems into AI solutions, including data collection, experiment design, and roadmap planning.
- Develop interpretable, modular, and scalable ML systems that deliver measurable business value.
- Work directly with customers and stakeholders to ensure deployed systems achieve their intended impact.
- Stay current with advancements in AI/ML, including LLMs, diffusion models, graph AI, and agent architectures.
- Propose and prototype new approaches for integrating emerging technologies into production products.
- Develop methods to quantify and communicate AI performance and business ROI.
- Promote responsible, ethical, and impactful AI practices across the organization.
- Proven track record of launching AI/ML products into production.
- Experience with core ML/AI tools:
Python, PyTorch, Tensor Flow / Keras, scikit‑learn, SQL, Spark. - Experience writing production‑grade Python (object‑ and function‑oriented).
- Hands‑on expertise with large‑scale ML systems, GenAI (LLMs, diffusion), agents, and graph‑based models.
- Experience designing and managing ML orchestration workflows and versioned pipelines (Airflow, ZenML, Kedro, dbt, etc.).
- Strong problem‑solving skills, adaptability, and a “hacker” mentality.
- Excellent communication skills—able to work with both technical and non‑technical stakeholders.
- Demonstrated thought leadership and innovation in applied AI.
Hybrid role based in New York City; open to remote U.S. candidates willing to travel monthly to our NYC office.
Interview Round- Phone Screen
- Peer Interview
- Founders' Interview
We are an equal opportunity employer and consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law. We actively encourage diversity, inclusion, and equitable hiring practices.
If you require accommodations during the hiring process, please reach out to our recruitment team at join
#J-18808-Ljbffr(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).