ML Engineer

Your Job

As a Machine Learning Engineer at Koch Capabilities India, you will ensure production machine learning solutions remain reliable, scalable, and trusted by the business teams who depend on them every day. You will partner closely with data scientists, data engineers, and business stakeholders to operationalize machine learning models, maintain healthy data pipelines, and drive adoption of AI-enabled solutions across manufacturing, procurement, supply chain, and research functions.

In this role, you will bridge the gap between model development and business value by owning deployment, monitoring, troubleshooting, and continuous improvement of production machine learning systems.

Our Team

You will be part of the Data & Analytics capability supporting INVISTA and other Koch companies through Koch Capabilities India. Our team partners with business and technology stakeholders to build, deploy, and support data-driven solutions that improve decision-making and create long-term value. We combine analytics, engineering, and domain expertise to deliver reliable and scalable AI and machine learning capabilities across global operations.

What You Will Do

• Monitor production data pipelines and resolve issues before they impact downstream models or business users.
• Maintain the reliability, performance, and availability of machine learning solutions in production environments.
• Identify model drift, data quality issues, and performance degradation, and implement corrective actions.
• Troubleshoot production incidents including failed pipelines, model retraining failures, stale datasets, and API or endpoint issues.
• Partner with stakeholders to understand business problems, evaluate available data, and define solution requirements.
• Assess whether business challenges are best addressed through machine learning, analytics, automation, reporting, or process improvements.
• Prepare and transform data, engineer features, and validate outputs to support advanced analytical and machine learning solutions.
• Deploy, monitor, and manage machine learning models using modern MLOps practices.
• Integrate model outputs into business processes and applications to drive adoption and measurable business outcomes.
• Contribute to the development of foundational machine learning solutions including regression, classification, clustering, anomaly detection, and forecasting models.
• Collaborate with cross-functional teams to continuously improve data, analytics, and AI capabilities.

Who You Are (Basic Qualifications)

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.
• 3+ years of experience deploying and supporting machine learning models in production environments.
• Experience deploying and supporting machine learning models in production environments.
• Strong Python programming skills with experience using libraries such as pandas, NumPy, scikit-learn, and visualization frameworks.
• Experience with machine learning techniques such as classification, regression, anomaly detection, time-series forecasting, natural language processing, or computer vision.
• Understanding of feature engineering, model evaluation, validation methodologies, and hyperparameter tuning.
• Strong SQL skills for data extraction, transformation, and analysis.
• Experience building and maintaining automated data pipelines.
• Knowledge of containerization, CI/CD practices, and model lifecycle management.
• Experience deploying solutions on cloud platforms such as AWS, Azure, or GCP.
• Strong problem-solving skills and ability to communicate effectively with technical and non-technical stakeholders.
• Demonstrated ownership mindset with the ability to proactively identify, communicate, and resolve issues.

What Will Put You Ahead

• Experience with Snowflake, including Snowpark ML, Tasks, Streams, Dynamic Tables, Stored Procedures, or UDTFs.
• Experience with Kubernetes, AWS Lambda, Step Functions, GitLab CI, ArgoCD, JFrog, or similar modern platform technologies.
• Familiarity with Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or deep learning frameworks such as PyTorch.
• Experience with model explainability and interpretability techniques such as SHAP.
• Knowledge of manufacturing, chemical processes, supply chain operations, or industrial data systems such as OSI PI or SAP.
• Experience building analytical applications and visualizations using Streamlit, Power BI, Sigma Computing, or similar platforms.
• Exposure to MLOps frameworks, model monitoring, and responsible AI practices.

At Koch companies, we are entrepreneurs. This means we openly challenge the status quo, find new ways to create value and get rewarded for our individual contributions. Any compensation range provided for a role is an estimate determined by available market data. The actual amount may be higher or lower than the range provided considering each candidate's knowledge, skills, abilities, and geographic location. If you have questions, please speak to your recruiter about the flexibility and detail of our compensation philosophy.

Who We Are

At Koch, employees are empowered to do what they do best to make life better. Learn how our business philosophy helps employees unleash their potential while creating value for themselves and the company.

Additionally, everyone has individual work and personal needs. We seek to enable the best work environment that helps you and the business work together to produce superior results.