Docket

Machine Learning Engineer

• Lead and architect IDP (Intelligent Document Processing) solutions: develop, train, and optimize robust pipelines for extracting unstructured data from complex documents, defining efficient fine-tuning, RAG, and computer vision strategies.
• Architect Agentic AI development: design and productionize complex agentic workflows using LangGraph, n8n, and others, ensuring state management, resilience, low latency, and failure handling in the orchestration of the formalization and credit pipeline.
• Model structured data for new AI products: build statistical pipelines and advanced analytical models on the data extracted by IDPs, transforming raw data into strategic business reports, market indices, and predictive intelligence.
• Ensure Quality, Observability, and Cost (Evals & FinOps): structure automated evaluation frameworks (LLM Evals) to measure hallucination, accuracy, and recall of models in production, optimizing token consumption and infrastructure costs.
• Autonomy and cross-functional collaboration: work directly with Product Managers, Engineering, and Technical Leadership to translate market pain points into viable architectures, participating actively from PoC design through final production delivery.
• Mentorship and technical culture: support the technical development of more junior team members, disseminating best practices for coding, modeling, and AI usage.

• Support the development of IDP (Intelligent Document Processing) solutions: Contribute to creating, training, tuning models and fine-tuning for extracting unstructured data from complex documents.
• Build the future of agentic AI: Assist in orchestrating workflows using frameworks such as LangGraph, n8n, and others, connecting document extraction to approval and formalization pipelines.
• Transform data into products: Apply statistical techniques and data analysis to the structured datasets produced by our IDPs, helping identify patterns and insights that will become new AI products for our clients.
• Collaborate with technical, product and commercial teams: Work side by side with Technical Leadership, Data Engineering, Product Managers and the Front-end team, evaluating, supporting and improving the transition of proofs of concept (PoCs) to production solutions.
• Ensure quality and monitoring: Help evaluate model outputs (LLMs, RAGs and classical models), test prompts and document processes, ensuring solutions are accurate and scalable.
• Learn and innovate: Stay up to date with the state of the art in Generative AI, bringing curiosity, ideas and proactivity to solve bottlenecks in our document pipeline.

Junior Machine Learning Engineer

Business Development Rep

• Generate a high‑value pipeline for the sales team through outbound prospecting in Enterprise accounts.
• Maintain a high level of activity (cold calls and emails) and be motivated to exceed daily, weekly and monthly goals and KPIs.
• Have an in‑depth understanding of our solutions to match clients' needs with the services offered by Docket.
• Be well versed in sales methodologies such as SPIN Selling and BANT and apply them in customer interactions.
• Prospect, qualify and hand off opportunities to Sales Executives.
• In addition to sending many emails, you will make a large number of calls — it is important to enjoy speaking on the phone.

Machine Learning Engineer

Junior Machine Learning Engineer

Business Development Representative, Mid-level