Machine Learning/AI Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and deploy a minimum of three (3) production-quality AI/ML models for applications such as predictive maintenance, anomaly detection, classification, forecasting, or optimization.

• Design, construct, and oversee comprehensive machine learning pipelines, covering data preprocessing, feature engineering, model training, evaluation, and deployment.

• Utilize deep knowledge in PyTorch and/or TensorFlow to develop and enhance sophisticated machine learning and deep learning models.

• Establish and maintain scalable model serving architectures, ensuring high availability, low latency, and secure inference in production settings.

• Work alongside data engineers to access, transform, and prepare extensive datasets for model training and inference.

• Collaborate with product owners, analysts, and stakeholders to convert business requirements into machine learning solutions.

• Track model performance in production, including drift detection, accuracy monitoring, and retraining strategies.

• Ensure adherence to federal security, privacy, and governance standards in all AI/ML implementations.

• Engage in Agile development processes, including sprint planning, design reviews, and technical demonstrations.

• Document model architectures, training methodologies, and deployment processes for future maintenance and audit purposes.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, or a related field (or equivalent experience).

• Over 3 years of experience in machine learning, data science, or AI engineering roles.

• Demonstrated experience delivering production-grade machine learning models in practical environments.

• Expert-level proficiency in Python and ML frameworks (such as scikit-learn, TensorFlow, PyTorch).

• Advanced SQL development skills, including complex queries, performance tuning, and data transformation logic.

• Experience using Large Language Models (LLMs) in development.

• Knowledge of fundamental concepts like context windows, prompt design, and input/output structures, with the ability to effectively apply AI tools in developing and enhancing solutions.

• Experience in building and deploying models using scalable serving frameworks (for example, REST APIs, containerized deployments, or cloud-based inference services).

• Experience managing large-scale structured and unstructured datasets.

• Strong grasp of machine learning principles, including supervised/unsupervised learning, deep learning, model evaluation, and feature engineering.

• Experience in the federal government or other highly regulated environments with stringent security and compliance requirements.

• Excellent analytical and problem-solving abilities.

• Capability to convey complex technical concepts to non-technical stakeholders.

• Strong collaboration skills across engineering, data, and product teams.

• Ability to operate independently in a fast-paced, mission-driven environment.

• Attention to detail with a focus on model reliability and readiness for production.

• US Citizenship or Permanent Residency is required.

• Must reside within the Continental US.

• Depending on the government agency, specific requirements might include a public trust background check or security clearance.

🏝️ Benefits

• Health care

• Dental

• Vision

• Life insurance

• 401(k)

• Paid time off including PTO, holidays, and any other paid leave mandated by law