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# ML/AI Engineer

- **Company:** Deltek, Inc
- **Location:** United States
- **Experience:** Experienced
- **Salary:** $63,500.0 - $111,750.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Cloud Storage, Code Review, Databases, Data Cleansing, Extract Transform Load (ETL), Database Queries, Mobile Application Software, Python (Programming Language), PostgreSQL, Machine Learning, MySQL, Natural Language Processing, NumPy, Performance Tuning, Tensorflow, Azure Machine Learning, Software Deployment, Transaction Data, Unstructured Data, Data Logging, Data Processing, Google Cloud, Feature Engineering, Pytorch, Flask (Web Framework), Large Language Models, Model Validation, Fastapi, Pandas, Git Flow, Scikit Learn, Information Technology, Api Design, Restful APIs, Software Version Control, Data Pipelines, Unsupervised Learning, Microservices
- **Published:** June 2, 2026
- **Apply:** https://www.dice.com/job-detail/ac569e1c-605b-418b-b866-53bc15dbe1b8

## About the Role

* 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 Google Cloud Platform; experience with cloud storage, compute, and managed ML services
 * Version control and collaboration: Git workflows, agile methodologies, working in cross-functional teams
 * Bonus: Exposure to NLP techniques, LLMs, embedding models, or vector databases; experience in B2B SaaS environments
 * Education: BS in Computer Science, Data Science, Mathematics, or related technical field

## Description

* 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


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