Machine Learning Engineer

• Develop AI workflows, customize data pipelines, tune models, and engineer prompts to bring idea to prototype
• Work with subject matter experts to set up evaluation for AI workflows, ensuring rigor, quality and safety of content output
• Work with eng partners to integrate AI workflows into production
• Build and configure AI performance monitoring with proper reporting and alerts
• Optimize and maintain AI workflows for performance, reliability, and long-term scalability
• Conduct exploratory data analysis to answer key questions and test assumptions. Design experiments and build prototypes for proof-of-concept.
• Provide AI expert advice to product and eng partners in shaping product roadmap
• Partner closely with software eng, product, data eng, ML platform teams to scope and plan in execution
• Communicate timeline, milestones, findings w/ internal stakeholders
• Guide less experienced team members, sharing knowledge on LLM workflows and AI/ML model lifecycle
• Champion a culture of experimentation, continuous learning, and proactive problem-solving
• Stay current with emerging ML tools and technologies, integrating new techniques that elevate our product capabilities

Machine Learning Engineer, Applied AI

• Partner with AI/ML product teams to proactively identify the data needs for rapid experimentation and stable production deployment
• Ensure data availability by collaborating with Product teams
• Support Data Analysts, Data Scientists, MLOps engineers in developing optimized data models, pipelines and frameworks
• Build pipelines to ingest, clean, and transform structured, semi-structured, and unstructured data formats
• Conduct data profiling, validation, and anomaly detection
• Build Vector databases for semantic search and retrieval of unstructured content
• Collaborate with data scientists and ML engineers to design end-to-end generative AI solutions
• Build clean, error-free MVP ready data models

Machine Learning Analyst

• Design, develop, and deploy machine learning solutions and feature engineering pipelines.
• Configure, test, debug, deploy, document, and maintain ML pipelines, models and feature engineering modules while adhering to specific development best practices and quality standards.
• Work closely with data scientists, data engineers, and solution architects to develop technical design specifications for ML programs, focusing on efficient feature engineering and model deployment.
• Analyze large-scale datasets and validate the proposed ML solutions with both the architectural design and the business needs, ensuring model performance meets target metrics.
• Responsible for troubleshooting and issue analysis across the ML stack, including feature pipelines, model training, inference, and model monitoring, as well as coding, testing, and implementing model enhancements.
• Demonstrate a strong understanding of supervised, unsupervised, ensemble, and deep learning algorithms to design and implement effective ML solutions, with experience in feature engineering, model evaluation, and continuous performance optimization to meet business targets.
• Implement and maintain MLOps practices including experiment tracking, model versioning, A/B testing, and automated retraining pipelines.
• Thrive in a fast-paced agile development environment, driving iterative model improvements.
• Implement and maintain data governance and model monitoring frameworks to ensure model reliability, fairness, and compliance with business standards.
• Available to support/unblock planned model deployments and retraining cycles during off hours.
• Contribute to the evolution of our ML architecture, with a focus on MLOps principles and emerging technologies for feature stores.

MLOps Engineer

AI Engineer

• Design, develop, and deploy AI/ML models for production environments.
• Build and optimize AI-powered applications using large language models (LLMs) and generative AI tools.
• Develop intelligent automation workflows, chatbots, recommendation systems, and predictive analytics solutions.
• Fine-tune, evaluate, and improve machine learning models for performance and scalability.
• Collaborate with software engineers and product teams to integrate AI features into existing platforms.
• Work with structured and unstructured datasets for training and inference pipelines.
• Implement prompt engineering strategies and retrieval-augmented generation (RAG) systems.
• Monitor AI systems, troubleshoot issues, and continuously improve model accuracy and efficiency.
• Stay updated with the latest advancements in AI, machine learning, and automation technologies.
• Maintain documentation for AI models, systems, and workflows.

• Build and extend the eval pipeline: how we measure task completion, catch regressions, and turn production failures into fixed behaviors.
• Work on context management: what the agent sees, when, and how we keep long-horizon tasks coherent without burning tokens.
• Design sub-agent patterns: when to fan out, how to compose specialized agents cleanly, and how to keep the parent agent in control of the outcome.
• Own document parsing: turning supplier-uploaded invoices, catalogs, and contracts into structured context the agent can reason over.
• Wrap Coupa supplier APIs as agent-callable CLI tools, with clean error surfaces and sensible defaults for an agent caller.
• Ship supplier-facing skills on top of the harness: the procedural instructions and tool compositions that let the agent handle specific tasks end-to-end.
• Debug messy production behavior: why did the agent take that path, where did it get confused, and what tool, context, or harness change fixes it?
• Partner with the senior engineer on harness architecture calls as you find gaps while working across the stack.

Lead AI Engineer

• Design and build the agent harness — skill loading, tool invocation, context management, the execution sandbox, compaction patterns and sub-agents.
• Stand up the evaluation pipeline: how we measure skill effectiveness, catch regressions, and turn production failures into fixed behaviors.
• Partner with product and engineering to ship the first 3–5 supplier-facing use cases (invoicing, catalog, strategic views) on top of the platform you build.
• Define and maintain the cloud deployment and configuration for the platform. How it gets to production, how it scales, and how it stays secure.
• Make architectural calls on runtime isolation, credential handling, audit logging, and tenant separation, in collaboration with DevOps specialists.
• Raise the bar for the rest of the team on how to build with agentic tooling, what to automate, what to verify, and what to leave to humans.

Senior Lead AI Engineer

• Architect, design and develop AI/ML solutions to solve novel business problems
• Implement traditional machine learning models and modern AI techniques, including LLMs, generative AI, RAG, and agentic AI systems
• Collaborate closely with product managers, engineers, data scientists, and business stakeholders
• Build robust, scalable, and maintainable AI systems
• Develop and execute rigorous model evaluation frameworks
• Transition AI prototypes into production-ready systems
• Contribute to documentation, governance, and compliance processes

Senior AI / ML Engineer

• System Administration & Optimization: Administer and optimize key GTM platforms (e.g., Salesforce, Marketo, Outreach, Gainsight), ensuring data integrity, system scalability, and user adoption.
• Strategic Planning & Roadmapping: Collaborate with GTM leadership to define system requirements, evaluate new technologies, and develop a strategic roadmap for GTM systems to align with business objectives.
• Integration & Data Flow Management: Design, implement, and maintain integrations between various GTM systems and other business-critical platforms, ensuring accurate and timely data flow across the organization.
• Process Improvement & Automation: Identify opportunities for process automation and efficiency gains within GTM workflows, leveraging system capabilities to streamline operations and improve team productivity.
• User Support & Training: Provide expert-level support to GTM teams, troubleshoot system issues, and develop training materials to ensure users are effectively utilizing GTM tools.
• Reporting & Analytics: Develop and maintain dashboards, reports, and analytics to provide insights into GTM performance, system utilization, and data quality.
• Vendor Management: Manage relationships with GTM system vendors, including contract negotiation, service level agreements, and product roadmap discussions.
• Compliance & Governance: Ensure GTM systems adhere to data privacy regulations (e.g., GDPR, CCPA) and internal governance policies.
• Project Management: Lead and manage GTM systems projects from conception to completion, including requirements gathering, solution design, testing, and deployment.

CX Technology Lead – AI

LLM Engineer

• Colaborar con ingenieros y partes interesadas no técnicas para garantizar que los resultados de la IA sean explicables, fiables y utilizables.
• Diseñar, probar y perfeccionar indicaciones de alta calidad para los modelos de aprendizaje de lenguaje natural (LLM) con el fin de apoyar la generación, el análisis y la automatización de contenido.
• Aplicar principios de arquitectura y diseño de software al integrar la IA en los sistemas.

Generative AI Engineer – Azure AI Search

• Diseñar y desarrollar modelos de Machine Learning para soluciones de ingeniería de alto impacto.
• Construir, entrenar y optimizar modelos de aprendizaje automático y profundo.
• Mantenerse al tanto de los últimos desarrollos en investigación y tecnología de AI/ML.
• Crear documentación completa de la arquitectura del modelo y procesos de entrenamiento.
• Presentar hallazgos y recomendaciones a audiencias técnicas y no técnicas.

• Diseño e implementación de prompts para modelos de lenguaje (LLMs), incluyendo técnicas de prompt chaining, evaluación y mejora iterativa.
• Colaboración interdisciplinaria con ingenieros y stakeholders para garantizar outputs de IA interpretables y alineados al negocio.
• Integración de IA en arquitecturas de software, aplicando principios de diseño y buenas prácticas de ingeniería.

See all jobs on JobTailor

Machine Learning Engineer, Applied AI

Machine Learning Analyst

MLOps Engineer

AI Engineer

Lead AI Engineer

Senior Lead AI Engineer

Senior AI / ML Engineer

CX Technology Lead – AI

Generative AI Engineer – Azure AI Search

AI Engineer

LLM Engineer, Prompting & AI Systems