Senior Staff ML Engineer: Agentic AI Leader

OpenKrill; United States; Remote; USD 250,000 - 295,000; Full time

Benefits offered by this job

Equity

Performance bonus

Flexible Time Off

Parental leave

Medical, dental, vision

401(k)

Commuter benefits

Calm wellness access

Pet insurance

Job summary

OpenKrill is seeking a Senior Staff Machine Learning Engineer in the United States to lead the architecture and delivery of agentic AI systems for processing global trade data. You will guide data ingestion, document understanding, and model inference while mentoring senior engineers and shaping product strategy.

Responsibilities include building scalable pipelines, refining LLMs with advanced training methods, and establishing robust evaluation/observability frameworks to ensure reliability,

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field, or equivalent practical experience.
• 10+ years of experience building and deploying machine learning systems in production, including a strong track record of delivering product-oriented ML solutions and recent experience with LLM-powered products.
• Deep expertise in PyTorch and the modern Python ML ecosystem, including Hugging Face, scikit-learn, NumPy, and Pandas or Polars.
• Hands-on experience developing production-grade LLM applications, including retrieval-augmented generation (RAG), tool and function calling, structured outputs, and agentic workflows.
• Proven experience deploying agentic systems in production, with planning, tool use, state management, recovery strategies, and human-in-the-loop processes.
• Practical experience adapting and post-training language models using SFT, DPO, RLHF, RLAIF, or reward modeling.
• Strong expertise in model evaluation, including evaluation suites, golden datasets, and LLM-as-a-judge pipelines.
• Sound technical judgment when selecting between proprietary model APIs, fine-tuned open-weight models, and classical ML approaches.
• Senior Staff-level leadership experience, including setting architecture direction across teams, mentoring engineers, and translating ambiguous problems into roadmaps.
• Strong problem-solving skills and a willingness to work directly with data and domain-specific challenges to achieve measurable business outcomes.
• Commitment to engineering quality, system reliability, operational supportability, and collaborative knowledge-sharing.
• Excellent written and verbal communication skills, with the ability to influence technical decisions across disciplines.
• Regular use of AI coding assistants such as Cursor or Claude Code as part of the development workflow.
• Preferred: multi-agent systems, LangGraph, hybrid retrieval, vector search, embeddings fine-tuning; vision-language models for invoices/bills/docs.
• Additional preferred: multilingual NLP, MLflow or Databricks Mosaic AI, AI guardrails, safe auditable systems.
• Familiarity with Python, Spark, Docker, Git, Kubernetes, Swagger/OpenAPI, AWS, Azure, Databricks, OpenSearch, PostgreSQL, FAISS, vLLM.

Responsibilities

• Define the technical vision, architecture, and roadmap for agentic AI systems that process global trade data and generate real-time risk assessments.
• Lead scalable data pipelines covering ingestion, document understanding, entity resolution, model inference, and intelligent routing.
• Develop and deploy production-grade ML systems transforming structured/unstructured trade data into actionable insights.
• Adapt and improve LLMs using SFT, DPO, RLHF, and domain-specific evaluation techniques.
• Build evaluation frameworks, golden datasets, tracing systems, and feedback loops to measure model quality and detect regressions.
• Design observability and monitoring to capture agent behavior and support reliable operation across workflows.
• Determine when to use frontier model APIs, fine-tuned models, or classical ML approaches balancing accuracy, latency, and cost.
• Provide technical leadership across engineering teams by establishing standards, mentoring, and helping with hiring.
• Collaborate with engineers, data scientists, product managers, and customers to turn business challenges into production-ready capabilities.
• Promote engineering excellence, maintainability, supportability, and knowledge sharing within the ML org.
• Explore new AI techniques to improve model capabilities and decision-making in complex trade environments.

Skills

PyTorch

Python

LLM apps

RAG

Production ML

Model evaluation

Agentic workflows

Observability

Education

Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field

Tools

Docker

Kubernetes

Spark

Git

OpenSearch

FAISS

Databricks

AWS

Azure

vLLM

LangGraph

Job description

OpenKrill is seeking a Senior Staff Machine Learning Engineer in the United States to lead the architecture and delivery of agentic AI systems for processing global trade data. You will guide data ingestion, document understanding, and model inference while mentoring senior engineers and shaping product strategy.

Responsibilities include building scalable pipelines, refining LLMs with advanced training methods, and establishing robust evaluation/observability frameworks to ensure reliability,