Senior Machine Learning Engineer
Autodesk
Job Summary
Autodesk is seeking a Senior Machine Learning Engineer to join their team, focusing on transforming water utility management with AI-driven solutions. The role involves integrating and optimizing AI models for predictive analytics and operational decision-making within production systems. The engineer will build scalable, cloud-based ML pipelines using Python and AWS, collaborate on the entire ML lifecycle, and work with complex datasets to extract actionable insights. This position requires an impact-driven innovator passionate about applying machine learning and software engineering to solve real-world challenges in critical infrastructure.
Must Have
- Implement, integrate, and optimize AI models for predictive analytics, operational decision-making, and anomaly detection within production systems.
- Build scalable, cloud-based ML pipelines and APIs using Python, FastAPI, and AWS services (e.g., SageMaker, Lambda).
- Collaborate on the end-to-end ML lifecycle: data ingestion, feature engineering, model evaluation, and deployment.
- Work with large, complex datasets (including time-series and sensor data) to extract actionable insights.
- Ensure seamless integration of AI components into our SaaS platform with high reliability and performance.
- Design and implement agentic workflows that enable autonomous decision-making and orchestration of AI-driven tasks.
- Contribute to backend architecture, algorithm design, and software engineering best practices.
- Implement robust testing strategies (unit, integration, performance) and CI/CD pipelines for production-grade systems.
- Stay ahead of emerging ML technologies and contribute to open-source projects.
Good to Have
- Experience with time-series forecasting, optimization algorithms, or reinforcement learning.
- Familiarity with distributed systems and containerization (Docker).
- Knowledge of Model Context Protocol (MCP) for integrating AI systems.
- Practical experience with multi-tenant SaaS applications.
Perks & Benefits
- Annual cash bonuses
- Commissions for sales roles
- Stock grants
- Comprehensive benefits package
Job Description
Position Overview
We are transforming how utilities manage one of the world’s most precious resources: water. Our AI-driven platform empowers water utilities to make smarter, real-time decisions for critical processes like demand forecasting and sewer overflows. By leveraging advanced machine learning and automation, we help utilities reduce costs, improve reliability, and minimize risks to public safety.
We’re also reimagining how the operational workforce of the 21st century interacts with critical infrastructure - building intelligent systems that shape the future. We’re looking for impact-driven innovators passionate about applying machine learning and software engineering to solve real-world challenges.
As a Machine Learning Engineer, you will integrate and optimize AI solutions that enhance operational decision-making for billions of dollars in water infrastructure. You’ll work on mission-critical systems using cutting-edge cloud technologies and ML frameworks in an agile environment.
Responsibilities
- Implement, integrate, and optimize AI models for predictive analytics, operational decision-making, and anomaly detection within production systems
- Build scalable, cloud-based ML pipelines and APIs using Python, FastAPI, and AWS services (e.g., SageMaker, Lambda)
- Collaborate on the end-to-end ML lifecycle: data ingestion, feature engineering, model evaluation, and deployment
- Work with large, complex datasets (including time-series and sensor data) to extract actionable insights
- Ensure seamless integration of AI components into our SaaS platform with high reliability and performance
- Design and implement agentic workflows that enable autonomous decision-making and orchestration of AI-driven tasks
- Contribute to backend architecture, algorithm design, and software engineering best practices
- Implement robust testing strategies (unit, integration, performance) and CI/CD pipelines for production-grade systems
- Stay ahead of emerging ML technologies and contribute to open-source projects
Minimum Qualifications
- Bachelor’s degree or Master's degree in Computer Science, Engineering, Data Science, or related field (or equivalent experience)
- 3-5+ years of experience in machine learning and software development for production systems
- Strong proficiency in Python and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch)
- Experience with cloud-based ML services (AWS SageMaker preferred)
- Solid understanding of data structures, algorithms, and software design principles
- Familiarity with SQL/NoSQL databases and handling large-scale datasets
- Experience building and deploying APIs and microservices
- Knowledge of CI/CD pipelines and version control (Git)
- Excellent communication and collaboration skills
The Ideal Candidate
- Experience with time-series forecasting, optimization algorithms, or reinforcement learning
- Familiarity with distributed systems and containerization (Docker)
- Knowledge of Model Context Protocol (MCP) for integrating AI systems
- Practical experience with multi-tenant SaaS applications
Salary transparency
Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.
Diversity & Belonging
We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging