We've grown to become the world's leader in producing, sourcing, distributing and marketing fresh Hass avocados. As a vertically integrated and public company, our total focus is avocados. We provide customers in over 25 countries with the complete package—year-round supply, global availability, and value-added services.

Our partners are passionate and experienced growers from the most ideal avocado growing regions in the world. To supply customers with the world's finest avocados, we operate packing facilities in five countries and own 11 regional ripening centers worldwide. Our distribution centers and transportation capabilities ensure peak eating-quality avocados from the tree to the customer. And when it comes to food safety, we adhere to the Good Agricultural Practices (GAP) program and Good Harvesting Practices (GHP). We proudly share responsibility with our growers to ensure total satisfaction for our customers.

JOB SUMMARY

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. You will partner closely with operations, finance, sales, sourcing and IT to translate business problems into AI solutions that improve operational decision-making. This role will also work with large operational datasets to develop AI-driven insights and automation.

ESSENTIAL DUTIES & RESPONSIBILITIES

1. 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.
2. 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).
3. Data & Modeling: Develop and maintain Python pipelines (ETL/ELT) and ML models; implement robust feature engineering and model monitoring across the ML lifecycle.
4. 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.
5. Platform Integration: Integrate AI into Power Platform solutions and line‑of‑business apps using Copilot Studio, Azure Cognitive Services, and enterprise connectors.
6. Autonomous Agents: Build task-oriented AI agents and automation workflows with human-in-the-loop controls, safety constraints, and auditability.
7. Context & Interoperability: Design context management patterns for AI systems and integrate enterprise data sources such as Fabric OneLake, Synapse, Databricks, SharePoint and Graph.
8. 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.
9. 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.
10. Observability & Governance: Implement telemetry (App Insights, Prometheus), responsible AI evaluations (fairness, safety, toxicity), RBAC/data classification, and evidence trails aligned to IT governance roles
11. Documentation & Enablement: Create runbooks, model cards, data contracts, and playbooks; mentor developers and citizen makers on safe and effective AI use.

MINIMUM QUALIFICATIONS & REQUIREMENTS

1. Experience: 5+ years in software/data engineering or machine learning
2. 2+ years building AI/ML or LLM-based systems in production environments.
3. Azure Stack: Hands‑on with Azure AI services, Azure Foundry, Azure Machine Learning, OpenAI on Azure, and Copilot Studio.
4. Lakehouse Expertise: Working knowledge of Lakehouse architecture and tools such as Microsoft Fabric, Databricks, and/or Azure Synapse.
5. DevOps/MLOps: Proficiency with Git, Azure DevOps (or GitHub), Agile methods (e.g., Jira), and CI/CD pipelines for analytical solutions.
6. Agents/Workflows: Proven experience building autonomous agents or AI‑driven workflows with safety and observability.
7. LLM Practice: Expertise in prompt engineering, fine‑tuning, RAG, and evaluation frameworks.
8. Lifecycle Mastery: Comprehensive understanding from experimentation through deployment, monitoring, and continuous improvement.

DESIRED SKILLS:

1. Strong Python development skills and experience with machine learning and LLM frameworks such as PyTorch, TensorFlow, or HuggingFace
2. Experience building LLM-powered applications, including prompt engineering, RAG pipelines, and evaluation frameworks
3. Familiarity with vector embeddings and semantic search using technologies such as Azure OpenAI or Azure AI Search
4. Strong understanding of forecasting and time-series modeling techniques
5. Experience building data products and pipelines using Fabric, Databricks, Synapse, or similar lakehouse architectures
6. Experience integrating AI systems with enterprise data sources and APIs
7. Experience implementing MLOps practices on Azure, including model registry, CI/CD pipelines, automated retraining, and monitoring
8. Familiarity with Azure DevOps or GitHub Actions for AI/ML lifecycle automation
9. Knowledge of data privacy, security, and responsible AI principles

Salary Range: $143,000 - $200,000

MISSION PRODUCE CALIFORNIA EMPLOYEE PRIVACY POLICY

This privacy policy ("Policy") sets out how Mission Produce uses and protects any information that you may give Mission Produce in the context of your employment, job application, or other similar working relationship with Mission Produce. This policy also applies to the information we collect about your emergency contacts and individuals for whom we administer benefits relating to your employment with us.

CATEGORIES OF PERSONAL INFORATION WE COLLECT:

1. Identifiers such as your name, postal address, internet protocol address, email address, social security number, driver’s license number, passport number, or other similar identifiers.
2. Sensitive information, such as your bank account number, health insurance information, or employment history.
3. Characteristics of protected classifications under California or federal law.
4. Internet or other electronic network activity information.
5. Audio, electronic, visual, or similar information.
6. Professional or employment-related information.
7. Inferences drawn from any of the above-listed categories of information

HOW WE USE YOUR PERSONAL INFORMATION

We use your personal information to facilitate your relationship with us, including to:

1. identify and recruit employees, including by conducting due diligence into employee backgrounds;
2. administer our benefit plans, including our health plans for dependents;
3. meet our payroll needs;
4. analyze your performance, conduct performance reviews, and adjust your role;
5. maintain records, such as licensure and credentialing records relating to your role;
6. support our HR functions, including handling employee claims, complaints, travel, and administering changes to employment status;
7. contact you regarding your work with and relationship to us and in emergency situations;
8. meet our legal requirements, such as confirming that you are eligible to work in the U.S.;
9. maintain the security and confidentiality of our systems and information, including but not limited to trade secrets;

If you have any questions, please contact Rachel Bryan at rbryan@missionproduce.com.

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