Applied AI Engineer

Applied AI Developer

About the Role

The Applied AI Developer is responsible for designing, building, and deploying machine learning and AI-powered user features within the SureTrend platform and supporting Hygiena's broader data intelligence initiatives. This role bridges data science and software engineering — translating research-grade models into production-ready systems that deliver real value to food safety customers. The Applied AI Developer collaborates closely with Product Managers, Data Analysts, and Engineering to identify high-impact AI opportunities and bring them to life.

Responsibilities

• Design, develop, and deploy machine learning models and AI features using Python (scikit-learn, PyTorch, TensorFlow, or equivalent frameworks). (35% of time)

• Collaborate with Product and Engineering to identify AI/ML use cases with measurable customer and business impact (e.g., anomaly detection, predictive alerts, NLP for compliance documents). (20% of time)

• Build and maintain ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment in Azure cloud environments. (20% of time)

• Integrate AI/ML capabilities into the SureTrend platform via APIs, working with .NET/C# and React-based services. (10% of time)

• Monitor model performance in production; design retraining pipelines and drift detection strategies. (10% of time)

• Document model methodologies, data requirements, and performance benchmarks; communicate findings to technical and non-technical stakeholders. (5% of time)

• Ensure compliance with organizational systems, programs, training, policies, and procedures; seek guidance as necessary.

• Actively support the safety program per the Safety Manual and IIPP.

• Carry out all responsibilities in an honest, ethical, and professional manner.

• Maintain essential job functions in a consistent state of alertness and safe manner.

• Handle other duties as delegated by management.

Supervisory Responsibilities

This position does not have direct supervisory responsibilities. Senior-level candidates may provide technical mentorship to Data Analysts on ML concepts and implementation.

Minimum Qualifications

Education

• Bachelor's or Master's Degree in Computer Science, Machine Learning, Data Science, or a related field required.

Experience

• Minimum of 3–5 years of applied ML or AI engineering experience, including:
• Strong Python development skills (pandas, NumPy, scikit-learn; PyTorch or TensorFlow preferred)
• End-to-end ML pipeline development: data preparation, feature engineering, model training, evaluation, and deployment
• Cloud-based ML infrastructure (Azure ML, Azure AI Services, or equivalent)
• RESTful API development for exposing model outputs to product surfaces

• Experience working in Agile teams and managing ML workstreams in Azure DevOps or Jira.

• Familiarity with LLMs, prompt engineering, or Retrieval-Augmented Generation (RAG) architectures is a strong plus.

• Knowledge of the food safety or life sciences domain is advantageous but not required.

Skills & Abilities

• Strong engineering discipline with the ability to build reliable, production-grade ML systems, not just experimental models.

• Excellent problem-solving skills; comfortable operating at the boundary of research and engineering.

• Clear communication of technical approaches and model outputs to diverse audiences including Product, Sales, and Customers.

• Collaborative mindset; works effectively across Data, Engineering, and Product teams.

• Intellectually curious and committed to staying current with advances in applied AI/ML.

• High ownership mentality — takes responsibility for model quality, performance, and business outcomes.

Working Conditions

• Standard business hours, Monday through Friday, with flexibility for model training runs and production deployments.

• Hybrid work model: combination of in-office presence in Camarillo, CA and remote work.

• Occasional travel for industry conferences or team meetings.

Physical Demands

• This position is considered light work — exerting up to 20 pounds of force occasionally, and/or up to 10 pounds of force frequently.

• Required to have close visual acuity to perform activities such as viewing a computer screen for extended periods.

• Frequently required to maintain a static position, talk, hear, see, and perform repetitive motions.

Work Environment

• Typical office or administrative work environment. Not substantially exposed to adverse environmental conditions.

• Hybrid work model: combination of in-office (Camarillo, CA) and remote work, subject to team and business needs.