We are looking for an ML Ops Engineer to join our Data Science and Analytics team to own and support the deployment, management, and optimization of machine learning models and analytics frameworks across of our organization. The role will bridge the gap between data science, technical stakeholders, and operations to ensure a smooth and efficient lifecycle for ML models. This role will be responsible for building and maintaining scalable ML pipelines, hosting web-apps, ensuring efficient model tracking and lifecycle management using CI/CD and ML Ops best practices.

As an ML Ops Engineer, you will play a crucial role in supporting the organizations analytics vision by working closely with data science, software engineering, product, and data engineering to execute on data-driven initiatives. You will be responsible for designing and engineering deployment solutions for all our ML and data driven initiatives and ensure that models are deployed, monitored, and updated efficiently and effectively. The ideal candidate will have deep understanding of big data processing framework, experience deploying and tracking both API based and batch processing models. The ideal candidate will also have a deep understanding of data management, software development, and cloud computing.

What you'll do

• ML & Analytics Deployment: Manage the end-to-end lifecycle of machine learning models, simulation models, and analytics insights from development to production

• Big Data Processing: Utilize Apache Spark and Databricks for large-scale data processing, model training, and real-time analytics

• Model Performance & Monitoring: Implement CI/CD pipelines for ML models, ensuring scalability, reliability, and version control

• Streamlit App Development: Build interactive Streamlit applications to facilitate internal analytics, reporting, and decision-making tools

• Infrastructure & Automation: Design and manage MLOps infrastructure, including automated workflows, monitoring systems, and deployment strategies

• Collaboration: Work closely with data scientists, data engineers, and software engineers to integrate ML models into production systems and analytics platforms

• Writing high quality, testable, maintainable production code

• Develop automated, testable, and scalable solutions and data products

• Taking ownership and leading the development various projects and initiatives throughout the organization working with our product team

• Be a culture-setter, creating a collegial and supportive environment where teammates can develop as professionals and do great work

• Stay up to date with the latest developments in machine learning and cloud computing technologies
  

What you'll bring

• 5+ years of experience in MLOps, Data Engineering, Data Science, or related roles

• Familiarity with Big Data Frameworks and Distributed computing tools (Spark, PySpark, HDFS, MapReduce, Hive, Databricks, etc.) and building/deploying Cloud applications

• Strong Software Engineering background, including experience with data modeling, algorithms, and software quality processes (e.g. CI/CD tools, code reviews, testing & deployment automation, etc.)

• Knowledge and experience working with ML Frameworks (e.g. Scikit-learn, PyTorch, TensorFlow) and deploying trained models using serving platforms (e.g. MLflow)

• Experience deploying, tracking, and managing ML models in production

• Hands-on experience with CI/CD pipelines (GitHub Actions, Jenkins, or similar) for ML Deployment

• Knowledge of cloud platforms such as AWS, Azure, GCP (we use AWS)

• Familiarity with distributed computing, data streaming, and time-series forecasting models

• Proficiency in various python visualization and dashboarding packages (e.g. Plotly, Matplotlib, Streamlit) and experience developing web apps for internal stakeholder insight delivery

• Ability to communicate systems/data concepts and designs to a wide range of stakeholders

• Ability to develop strong working relationship with internal stakeholders such as product, data engineering and software engineering

• Strong problem-solving skills and ability to troubleshoot complex issues

• Experienced in developing BI reports using Power BI, Looker or other related services

• Experience in the Power & Energy industry, working with forecasting models, customer analytics, etc. a plus

• Experience deploying LLMs, RAG-based AI systems, and Generative AI models in production a plus

• Databricks experience a plus
  

Success Metrics

• Model Deployment: Deploy 2-3 new ML models quarterly with 99%+ uptime across all production models

• Code Quality: Achieve and maintain 80%+ test coverage across the data science codebase

• Analytics Applications: Deploy 5+ Streamlit apps/dashboards with consistent monthly active usage

• Model Monitoring: Implement monitoring and drift detection for 100% of models within 30 days of deployment

• AI Agent Infrastructure: Establish organization-wide MLOps framework for AI agent testing, tracking, and deployment

Location

• Serbia

What you'll love

• Our culture. We're friendly, transparent, and love to innovate together.
• Flexible work-life balance.We embrace the mix of working remote and from the office.
• Professional development opportunities.We love to grow together.
• A chance to make a difference. We're a sustainably-driven company rethinking what's possible in Energy.
• Competitive compensation. We reward performance with annual bonuses and salary increases.
• Health Benefits. We promote your wellbeing with paid vacation and premium private medical insurance for you and your family.
  

About Us

Rhythm is a renewable energy and technology company empowering you to take control of your budget and your footprint. We combine energy market expertise with technology, design, and data science to create best-in-class products and services that are simple, delightful, and seamlessly integrated with the rhythm of your life. Our mission is to upend the energy status quo by setting a new standard of service excellence and customer partnership. We are a mission-driven, results-oriented group of engineers, businesspeople, designers and artists who love solving tough problems, all while making a positive impact on our communities.