ML Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Address intricate technical challenges utilizing Appian and its associated platforms.

• Guide junior developers and perform peer code evaluations.

• Create and implement business logic, process models/flows, and user interface screens within a BPM-centric system.

• Provide technical direction to Agile development teams.

• Develop architectural frameworks in accordance with industry-standard practices.

• Troubleshoot systems integration challenges and convey technical concepts to senior client leadership.

• Design, train, test, and enhance machine learning models for predictive analytics, classification, and data-informed decision-making.

• Assess model performance, accuracy, and dependability while pinpointing areas for enhancement.

• Facilitate scalable, reusable machine learning capabilities.

• Aid in data ingestion, preprocessing, normalization, validation, feature engineering, data enhancement, and reusable data pipelines.

• Connect machine learning models with data pipelines, APIs, and application services.

• Assist in model packaging, version control, deployment automation, and continuous integration/continuous deployment (CI/CD) enhancements.

• Support deployment, troubleshooting, and readiness for production across development, testing, and production environments.

• Formulate and implement model testing and validation protocols.

• Supervise model outputs, data quality, defects, optimization prospects, and ongoing enhancement efforts.

• Collaborate with data engineers, software developers, architects, and product stakeholders.

• Convert business requirements into machine learning experiments, technical designs, and implementation tasks.

• Participate in technical planning, solution design, and delivery of machine learning capabilities.

• Document model architecture, experiments, evaluation outcomes, deployment processes, and technical decisions.

• Maintain technical documentation and share best practices and lessons learned.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related technical discipline.

• Equivalent combinations of relevant education, technical training, and professional experience may be acceptable.

• Proficient in developing, training, evaluating, and optimizing machine learning models using Python along with scikit-learn, pandas, and NumPy.

• Practical experience with Databricks for data processing, model development, experimentation, and machine learning workflows.

• Background in data preprocessing, feature engineering, data validation, and working with structured and semi-structured datasets.

• Knowledge of machine learning model deployment, REST APIs, and integration with data pipelines or application services.

• Familiarity with Git and GitHub.

• Experience in developing or maintaining CI/CD workflows utilizing GitHub Actions.

• Understanding of machine learning model evaluation metrics, testing methodologies, and performance monitoring.

• Skilled in writing clean, maintainable, and well-documented Python code.

• Strong analytical, problem-solving, troubleshooting, and communication abilities.

• Capacity to collaborate with cross-functional teams, including ML engineers, data engineers, software developers, and product stakeholders.

• Ability to work effectively in a collaborative Agile team environment.

• Candidates must be U.S. Citizens or Legal Permanent Residents (Green Card status) for three years and must be compliant with Federal Tax obligations.

🏝️ Benefits

• Comprehensive benefits package.

• Exceptional training and career development opportunities.

• Flexible work schedules.

• Competitive compensation package.

• Employee-centric environment promoting work-life balance, health, engagement, collaboration, and curiosity.