Key skills
Machine Learning EngineeringPython ProgrammingAPI DevelopmentData ProcessingCloud PlatformsVersion ControlNLP TechniquesAgile MethodologiesEducation in Technical FieldCollaboration SkillsPythonSQLAIMachine LearningMLNLPPyTorchTensorFlowscikit-learnPandasNumPyETLFastAPIFlaskAWSAzureGCPCloud StoragePostgreSQLMySQLRESTfulGitPerformance OptimizationSaaSERPAgileCollaboration
About this role
Deltek, Inc. is a recognized global standard for project-based businesses, delivering software and information solutions to help organizations achieve their purpose. The ML/AI Engineer will develop and deploy machine learning models, build data pipelines, and create production-ready ML services while collaborating with data scientists and optimizing models for performance.
Responsibilities:
- Develop and deploy machine learning models for classification, regression, forecasting, and NLP tasks using production-grade code and best practices
- Build data pipelines for ML model training and inference; work with structured and unstructured data from multiple enterprise systems
- Implement model training workflows including data preprocessing, feature engineering, hyperparameter tuning, and model evaluation
- Create production-ready ML services with RESTful APIs that can be consumed by web and mobile applications; ensure proper error handling, logging, and monitoring
- Work with large-scale datasets from enterprise ERP systems; process time-series data, transactional data, and unstructured documents
- Collaborate with data scientists to productionize research models; optimize models for latency, throughput, and cost
- Participate in code reviews and contribute to team's ML engineering practices; document solutions and share knowledge with team members
- Support deployed models including troubleshooting, performance optimization, and implementing improvements based on production metrics
Requirements:
- 2-4 years of ML engineering experience with hands-on model development and production deployment
- Strong Python programming: Experience with scikit-learn, pandas, numpy; familiarity with PyTorch or TensorFlow
- ML fundamentals: Solid understanding of supervised/unsupervised learning, model evaluation, cross-validation, and feature engineering
- API development: Experience building RESTful APIs (Flask, FastAPI, or similar); understanding of microservices architecture
- Data processing: SQL proficiency; experience with data pipelines, ETL processes, and working with databases (PostgreSQL, MySQL, or similar)
- Cloud platforms: Working knowledge of AWS, Azure, or GCP; experience with cloud storage, compute, and managed ML services
- Version control and collaboration: Git workflows, agile methodologies, working in cross-functional teams
- Education: BS in Computer Science, Data Science, Mathematics, or related technical field
- Bonus: Exposure to NLP techniques, LLMs, embedding models, or vector databases; experience in B2B SaaS environments