[Remote] ML/AI Engineer

Note: The job is a remote job and is open to candidates in USA. Deltek delivers software and information solutions for project-based businesses. The ML/AI Engineer will develop and deploy machine learning models, build data pipelines and production-ready ML services, and collaborate with data scientists to optimize and support deployed models.

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

Skills

• 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

Benefits

• Certain roles are eligible for additional rewards, including incentive compensation and equity.
• Employees have access to healthcare benefits
• A 401(k) plan and company match
• Paid vacation time and holidays
• Well-living programs
• Short-term and long-term disability coverage
• Basic life insurance
• Tuition reimbursement

Company Overview