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ML/AI Engineer

Deltek, Inc.
Remote, USA
Full-time
Entry · 2+ years experience
Remote
USD 63500-111750 yearly / year
Discovered 1 weeks ago
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Position 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

Qualifications

  • 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
  • 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

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