Senior AI/ML Engineer

New York

Software Engineering

Permanent

Our client, a venture-backed AI SaaS startup, are hiring a Senior AI/ML Engineer to join their product team in New York. The successful candidate will have the opportunity to tackle greenfield challenges and build core systems from the ground up.

Responsibilities

Take ownership of the AI stack, including selecting models, vector stores and cloud infrastructure to build a secure, high-performance pipeline.
Manage the full AI workflow, including data ingestion, cleaning, training, evaluation, deployment, monitoring and fine-tuning.
Operationalize AI by implementing CI/CD for models and data, ensuring reproducible experiments, monitoring for drift and maintaining usage dashboards.
Optimize systems for enterprise requirements, balancing latency, cost, data privacy and compliance-friendly logging.
Collaborate closely with product and engineering leadership to prioritize and execute high-impact initiatives.
Make pragmatic technical decisions in ambiguous environments, balancing technical elegance with business needs.
Help shape the engineering culture, tooling and processes in a fast-growing, early-stage startup.

Skillset

Over 7 years of professional experience, including 5 years developing clean, production-ready code for distributed, cloud-native systems.
At least 2 years of hands-on experience deploying LLM pipelines in production, with strong knowledge of tokenization, context windows, sampling strategies and common failure modes.
Proven track record in shipping generative AI or NLP products that meet real-world constraints such as latency, cost and data privacy.
Deep expertise in LLM tuning and retrieval, including prompting, RAG, embeddings, fine-tuning and hallucination mitigation.
Strong expertise of broader ML/data science experience, transforming raw data into robust models.
Experience in ML Ops, including CI/CD for models, experiment tracking, and production monitoring.
Strong product instincts, able to prototype quickly, iterate and collaborate closely with domain experts.
Demonstrated technical leadership through setting engineering standards, writing clear documentation and mentoring team members.
Proficiency with ML/LLM tools and libraries, with the ability to explain complex code and system behavior clearly.