The Machine Learning Engineer is responsible for developing, implementing, and productizing machine learning models that deliver business value. This role focuses on transforming machine learning prototypes into scalable, production-grade solutions. The ML Engineer works closely with data scientists, software engineers, and product teams to ensure that AI/ML models are effectively integrated into products, services, and applications, enabling data-driven decisions, and enhancing customer experiences.
What You Will Be Doing
- Productize ML Models: Work alongside data scientists who originate and design machine learning models to take these prototypes from concept to production-ready solutions. Focus on building scalable and efficient models for integration into live environments.
- End-to-End Model Deployment: Help deploy machine learning models into production environments, ensuring that they function reliably and are easily maintainable. This includes some DevOps practices such as CI/CD pipelines for model deployment.
- Data Preparation and Feature Engineering: Work with data scientists to preprocess, clean, and transform data to prepare it for production-grade machine learning models.
- Collaborate with Product Teams: Support product managers and stakeholders in defining model requirements and ensuring alignment with product goals.
- Model Optimization and Scaling: Assist in optimizing machine learning models to improve performance and scalability for large-scale production environments.
- Build and Maintain ML Pipelines: Help build and maintain ML pipelines to automate model training, testing, and deployment, incorporating DevOps principles to streamline processes.
- Monitoring and Maintenance: Monitor deployed models, check for performance drift, and work on necessary model updates, integrating monitoring tools for tracking model health.
- Model Evaluation and Reporting: Assist in evaluating model performance, analyzing metrics, and suggesting improvements.
- Documentation and Best Practices: Support documentation efforts related to model deployment processes, performance metrics, and best practices.
- Stay Current: Learn about emerging trends in AI/ML technologies and apply new methods to improve product offerings.
Your Qualifications
- Experience: 0-2 years of experience in machine learning engineering or a related field.
- Education: Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
- Technical Expertise: Basic understanding of machine learning algorithms, deployment practices, and integration.
- Product Focus: Some exposure to integrating machine learning models into products or production systems.
- Enthusiasm for AI/ML: Passion for AI/ML and a desire to contribute to solving business problems through machine learning.
- DevOps Exposure: Familiarity with DevOps practices in model deployment, including CI/CD pipelines, version control, and automated testing.
A few things we have to offer:
- Competitive compensation
- Great Healthcare + Dental + Vision
- Flexible PTO
- Culture of support, encouraging Life-Work balance
- 401k match
- FSA and HSA options
- Employee Assistance Program
- Paid Parental Leave
- Representing a company with 4,000+ clients and a 99% retention rate
- Accelerated title and salary growth potential
- A fun and energetic work environment that makes you excited to go to work every day
Top Skills
What We Do
Cleo is an ecosystem integration software company focused on business outcomes, ensuring each customer’s potential is realized by delivering solutions that make it easy to discover and create value through the movement and integration of B2B enterprise data. Cleo gives customers strategic, “outside-in” visibility into the critical end-to-end business flows happening across their ecosystems of partners and customers, marketplaces, and internal cloud and on-premise applications. Our solutions empower teams to drive business agility, accelerate onboarding, facilitate modernization of key business processes, and capture new revenue streams by reimagining and remastering their digital ecosystem through robust application, B2B, and data integration technologies.
Cleo Integration Cloud (CIC) is a cloud-based integration platform, purpose-built to design, build, operate and optimize critical ecosystem integration processes. The CIC platform brings end-to-end integration visibility across API, EDI and non-EDI integrations that gives technical and business users the confidence to rapidly onboard trading partners, enable integration between applications, and accelerate revenue-generating business processes. On the platform, businesses have the choice of self-service, managed services, or a blended approach – ensuring complete flexibility and control over their B2B integration strategy.
Cleo isn't just about EDI, iPaaS, API integration, or managed integration services. Rather we are about blending the best elements of these traditional integration technologies into a single platform, so organizations can connect and transact business across their entire ecosystem with complete confidence.
Why Work With Us
Cleo’s people share a genuine respect for each other and for the future we’re helping our customers to create. Beyond guiding how we act, and more important than driving us to deliver solutions that help our company and our customers succeed, our core focus on Appreciation creates something even more essential, for everyone: enduring value.
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Cleo Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.