Machine Learning Solutions Lead Specialist Engineer

Job Title: Machine Learning Solutions Lead Specialist Engineer

Location: Boulder, CO

Experience: 12+ Years

Employment Type: Contract

Interview Type: In-Person or Webcam

Job Summary

We are seeking an experienced Machine Learning Solutions Lead Specialist Engineer to architect and deliver advanced machine learning and AI-driven solutions across complex enterprise environments. The ideal candidate will have deep expertise in machine learning frameworks, scalable model deployment, cloud-based ML platforms, and experience leading teams to translate business challenges into actionable ML strategies. This role involves end-to-end project ownership including problem definition, data engineering collaboration, model development, MLOps automation, and implementation of production-ready ML systems.

Key Responsibilities

• Lead the design, development, and deployment of scalable machine learning models, algorithms, and advanced analytics solutions.
• Work closely with business stakeholders to identify opportunities for ML-driven automation and intelligent insights.
• Drive end-to-end ML lifecycle including data exploration, feature engineering, model training, validation, and production deployment.
• Architect AI/ML systems using modern cloud platforms such as AWS, Azure, or Google Cloud.
• Implement MLOps best practices for CI/CD pipelines, model versioning, monitoring, and automated retraining.
• Develop reusable ML frameworks, tools, and libraries to support predictive analytics and real-time decision systems.
• Collaborate with data engineers, data scientists, and software development teams to integrate models within enterprise platforms.
• Conduct performance tuning, evaluation, and testing of ML models to ensure accuracy, reliability, scalability, and ethical compliance.
• Mentor and provide technical leadership to junior engineers and data science team members.
• Document solution architectures and present technical strategies to leadership and cross-functional teams.
  
  

Required Qualifications

• 12+ years of experience in machine learning, artificial intelligence, or advanced data science roles.
• Strong expertise in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, and XGBoost.
• Solid understanding of distributed computing technologies such as Spark, Ray, or Dask.
• Hands-on experience with cloud-based ML platforms including AWS SageMaker, Azure ML, or GCP Vertex AI.
• Proven experience building and deploying large-scale ML pipelines and production-grade AI solutions.
• Strong background in statistics, probability, optimization techniques, and feature engineering methods.
• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Docker, and Kubernetes.
• Strong problem-solving, analytical, and communication skills.
  
  

Preferred Skills

• Experience working with LLMs, generative AI, and transformer-based architectures.
• Familiarity with real-time inference systems, streaming platforms, and event-driven processing such as Kafka or Flink.
• Experience with data governance, model explainability, fairness, and compliance frameworks.
• Knowledge of domain-specific ML applications such as forecasting, recommendation engines, NLP, computer vision, or reinforcement learning.
• Previous experience in leading AI-driven transformation programs or consulting environments.
• Advanced degree (Master's or Ph.D.) in Computer Science, Data Science, Machine Learning, Mathematics, or related field.