ML Engineer

• Solve highly complex technical problems using Appian and supporting platforms
• Mentor junior developers and conduct peer code reviews
• Design and develop business logic, process models/flows, and UI screens in a BPM-based system
• Provide technical leadership to Agile development teams
• Design architectural frameworks using industry-standard methodologies
• Resolve systems integration issues and present technical material to senior client leadership

Machine Learning Development & Optimization

• Develop, train, test, and optimize machine learning models to support predictive analytics, classification, and data-driven decision-making.
• Evaluate model performance, accuracy, and reliability to identify opportunities for improvement.
• Support the development and enhancement of scalable, reusable ML capabilities.
• Data Engineering & Feature Development
• Support data ingestion, preprocessing, normalization, validation, and feature engineering across multiple data sources.
• Develop data enrichment capabilities to improve model performance and analytical insights.
• Assist in building reusable data pipelines and preparing datasets for model training, evaluation, and inference.

ML Integration & CI/CD Support

• Integrate ML models with data pipelines, APIs, and application services to support operational use cases.
• Support model packaging, version control, deployment automation, and CI/CD pipeline improvements.
• Assist with deployment, troubleshooting, and production readiness activities across development, test, and production environments.

Testing, Validation & Performance Monitoring

• Develop and execute model testing and validation procedures to assess accuracy, reliability, and performance.
• Monitor model outputs and identify data quality issues, defects, and opportunities for optimization.
• Support ongoing model evaluation, maintenance, and continuous improvement.

Agile Team Collaboration

• Collaborate with data engineers, software developers, architects, and product stakeholders to align ML solutions with business and technical requirements.
• Translate business needs into ML experiments, technical designs, and implementation tasks.
• Contribute to technical planning, solution design, and delivery of new ML capabilities.

Documentation & Knowledge Management

• Document model architecture, experiments, evaluation results, deployment procedures, and technical decisions.
• Maintain technical documentation and implementation guidance to support knowledge transfer and maintainability.
• Share findings, best practices, and lessons learned to improve team effectiveness and consistency.

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related technical field.
• Equivalent combinations of relevant education, technical training, and professional experience may be considered.
• Experience developing, training, evaluating, and optimizing machine learning models using Python and common ML libraries such as scikit-learn (sklearn), pandas, and NumPy.
• Hands-on experience with Databricks for data processing, model development, experimentation, and ML workflows.
• Experience with data preprocessing, feature engineering, data validation, and working with structured and semi-structured datasets.
• Familiarity with ML model deployment, REST APIs, and integration with data pipelines or application services.
• Experience with Git and GitHub for source control, collaboration, and code management.
• Experience developing or maintaining CI/CD workflows using GitHub Actions, including automated testing, build processes, and deployment pipelines.
• Understanding of ML model evaluation metrics, testing methodologies, and model performance monitoring.
• Experience writing clean, maintainable, and well-documented Python code.
• Strong analytical, problem-solving, troubleshooting, and communication skills.
• Ability to collaborate effectively with cross-functional teams, including ML engineers, data engineers, software developers, and product stakeholders.
• Ability to work collaboratively in an Agile team environment.

• Relevant certifications or specialized training in machine learning, Databricks, cloud technologies, or MLOps.
• Experience in government contracting, regulated industries, or large enterprises
• Familiarity with identity, access management, data platforms, or enterprise SaaS ecosystems
• Experience working with Jira and Confluence

• Candidates must be a US Citizen or a Legal Permanent Resident (Green Card status) for 3 years and be Federal Tax compliant.