Senior AI/ML Engineer

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.

Benefits

• Salary: $160k – $220k DOE.

• Equity.

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