AI / Machine Learning Engineer

Job title: AI / Machine Learning Engineer Job type: Permanent Salary: $170,000 - $190,000 + bonus Role Location: Greater Los Angeles Area, California, United States Visa

: Full US Work Authorization required (no sponsorship provided) The company: Our client is the world’s leader in producing, sourcing, distributing, and marketing fresh avocados. As a vertically integrated and public company, their total focus is on avocados. They provide customers in over 25 countries with year-round supply, global availability, and value-added services. Their partners are passionate and experienced growers from the most ideal avocado growing regions in the world. The company operates packing facilities in five countries, owns 11 regional ripening centers worldwide, and maintains robust distribution and transportation capabilities to deliver peak eating-quality avocados from the tree to the customer. They adhere to the highest food safety standards through Good Agricultural Practices & Good Harvesting Practices. Role and

: The AI / Machine Learning Engineer designs, builds, and operates intelligent solutions using Azure AI services, Azure AI Foundry, Copilot Studio, and OpenAI on Azure. This role delivers production-grade AI systems, including LLM applications, AI agents, forecasting and time-series models, and lakehouse data products that automate decisions and transform business workflows. The successful candidate will partner closely with operations, finance, sales, sourcing, and IT teams to translate business problems into AI solutions that improve operational decision-making and deliver AI-driven insights and automation from large operational datasets. Essential duties and

include: • Solution Engineering: Design and implement AI/ML solutions with Azure Machine Learning, Azure AI Foundry (AI Studio), OpenAI on Azure, and Copilot Studio—delivering resilient, observable, and cost-optimized applications. • LLM Applications: Build, fine-tune, and evaluate LLM-based applications for internal and customer-facing use cases (retrieval-augmented generation, function calling, tool use, guardrails, multi-turn workflows). • Data & Modeling: Develop and maintain Python pipelines (ETL/ELT) and ML models; implement robust feature engineering and model monitoring across the ML lifecycle. • Forecasting: Deliver demand prediction, sales forecasting, and operational planning models using classical and machine learning time-series techniques; establish backtesting, drift detection, and continuous retraining. • Platform Integration: Integrate AI into Power Platform solutions and line-of-business apps using Copilot Studio, Azure Cognitive Services, and enterprise connectors. • Autonomous Agents: Build task-oriented AI agents and automation workflows with human-in-the-loop controls, safety constraints, and auditability. • Context & Interoperability: Design context management patterns for AI systems and integrate enterprise data sources such as Fabric OneLake, Synapse, Databricks, SharePoint and Graph. • Lakehouse Architecture: Design scalable data products on Fabric/Databricks/Synapse, including medallion layers, Delta/Parquet formats, vector storage, and streaming ingest for real-time signals. • MLOps & DevOps: Build CI/CD for models and prompts (Git/GitHub/Azure DevOps), environment provisioning (Terraform/Bicep), automated tests, A/B and canary deployments, and rollbacks. • Observability & Governance: Implement telemetry (App Insights, Prometheus), responsible AI evaluations (fairness, safety, toxicity), RBAC/data classification, and evidence trails aligned to IT governance roles. • Documentation & Enablement: Create runbooks, model cards, data contracts, and playbooks; mentor developers and citizen makers on safe and effective AI use.