Machine Learning Engineer

eNGINE
builds Technical Teams. We are a Solutions and Placement firm shaped by decades of interaction with Technical professionals. Our inspiration is continuous learning and engagement with the markets we serve, the talent we represent, and the teams we build. Our Consulting Workforce is encouraged to enjoy career fulfillment in the form of challenging projects, schedule flexibility, and paid training/certifications. Successful outcomes start and finish with
eNGINE
.

eNGINE
is hiring a Machine Learning Engineer who will own the full lifecycle of advanced ML systems, from research and prototyping through production deployment. This engineer will build robust, scalable AI solutions for time series forecasting, product matching, agent-based systems, and intelligent retail automation. This role requires candidates to be local to the greater Pittsburgh area and able to come into the office 1-2x/month.

What You’ll Do

• Design, build, and deploy production-grade ML models used by live retail customers
• Convert research concepts into scalable, high-performance production systems
• Develop models for time series forecasting, embeddings, retrieval, matching, optimization, and reinforcement learning
• Build AI agents that interact with APIs and perform reasoning & decision-making
• Architect real-time and batch pipelines for model inference
• Build out MLOps pipelines (training, testing, monitoring, automated retraining)
• Collaborate cross-functionally across Product, Engineering, and Leadership
• Stay sharp on emerging AI/ML research and propose new solutions

Required Qualifications

• Bachelor’s or Master’s in CS, ML, AI, Data Science, or related field
• 3+ years professional ML Engineering experience
• Expertise in Python, NumPy, Pandas, scikit-learn
• Advanced deep learning experience, especially PyTorch
• Experience shipping ML models to production
• Strong background in time-series forecasting, optimization, and classical ML
• Hands-on experience with clustering, embeddings, dimensionality reduction
• LLM fine-tuning, agent-based systems, or generative AI experience
• MLOps experience: MLflow, Kubeflow, Airflow, Docker, Kubernetes
• Strong communication and collaboration skills

No C2C/Sponsorship/Relocation available.

Apply today and see how eNGINE can make a difference in your career!