Machine Learning Engineer

Company Description

Trusys is an AI safety and governance platform that helps enterprises deploy AI systems with confidence. The company provides a guardrail layer that integrates with LLM endpoints, voice bots, RAG pipelines, and agentic workflows to monitor and control AI behavior. Trusys runs proprietary hallucination detectors, adversarial red-team probes, and drift monitors to reduce risk and improve reliability.

Its outputs align with industry-standard frameworks such as the EU AI Act, NIST RMF, and MITRE, generating machine-verifiable evidence to support audits, compliance, and risk management teams. This environment offers opportunities to work on cutting-edge AI reliability challenges for global organizations.

Role Overview

We are looking for an *AI/ML Engineer* with hands-on experience in *Python, Java, Machine Learning, Azure, and Databricks* to design, develop, and deploy scalable AI/ML solutions.

### Key Responsibilities

• Develop and deploy ML/AI models and production-ready applications.
• Build data and ML pipelines using *Azure Databricks and Spark/PySpark*.
• Perform data preprocessing, feature engineering, model training, and optimization.
• Develop ML APIs and integrate models with enterprise applications.
• Work with Azure services for deployment, monitoring, and MLOps.
• Collaborate with data scientists, data engineers, and software engineering teams.

### Must-Have Skills

• *Python & Java*
• *Machine Learning / AI*
• *Microsoft Azure*
• *Azure Databricks*
• *SQL & PySpark*
• ML model development and deployment
• REST APIs, Git, and CI/CD

### Azure & Databricks Experience

Experience with relevant Azure technologies such as:

• Azure Machine Learning
• Azure Databricks
• Azure Data Factory
• Azure Data Lake Storage
• Azure Functions
• Azure DevOps
• Azure AI Services

Hands-on experience with Databricks capabilities including:

• PySpark / Apache Spark
• Delta Lake
• Databricks Workflows
• MLflow
• Data and ML pipelines
• Model development and deployment

### Good to Have

• MLOps
• Generative AI / LLMs / RAG
• Docker / Kubernetes
• Azure DevOps

### Education

• Bachelor’s/Master’s degree in *Computer Science, Engineering, Data Science, AI, or a related field*.