Software Developer 1, Machine Learning

What you will do

If you love solving complex problems analyzing complex datasets finding insights from data creating data model and learning new technologies this role is for you.

• As a software developer you are passionate about shipping large-scale software systems in a fast-paced environment but can balance longer term issues such as maintainability scalability and quality.
• You are fluent in Python have experience working with distributed computing big data frameworks and are familiar with Kubernetes and Docker. You have the ability and enthusiasm to learn new technologies whether they are infrastructure or language or platform and easily adapt to change.
• You have a good understanding of Cloud technologies and Cloud agnostic software architecture and have experience troubleshooting high scale solutions that are deployed and upgraded on a regular cadence.
• You are passionate for software reliability and know how to ensure user needs are met through cross-functional stakeholder understanding and engagement.
• You are excited about finding ways to develop product capabilities and tools that increase robustness of the user experience reduce the cost of troubleshooting or reduce the time required to address issues.
• You excel as a team player a quick starter and a problem solver. You thrive in cross-functional teams actively listening and contributing to discussions. Your expertise lies in engineering solutions for complex machine learning challenges developing Python-based applications containerizing apps with Docker orchestrating container swarms in Kubernetes and building Argo Workflows. These efforts play a key role in creating ML software systems that deliver critical value to the business and its customers.

What we are looking for

This role requires a strong mix of data science expertise software engineering skills and problem-solving ability to build scalable production-grade solutions.

Education & Experience:

• • Bachelors or Masters degree in Computer Science Software Engineering Data Science or a related field or equivalent practical experience.
  • 2-5 years of relevant.

Technical Skills:

• • Agentic & Modern AI Frameworks:Practical experience building solutions using agentic AIpatterns RAG vector databases and orchestration frameworks like LangGraph/GoogleADK/OpenAI Agent SDK including prompt engineering and context engineering for production ofthe agentic workflows.
  • AI Driven Software Development:Experience in leveraging agentic software development tools -such as GitHub Copilot Claude Code or other autonomous agents - to accelerate delivery of newfeatures and resolution of issues.
  • Good programming skills in Python.
  • Experience with developing REST APIs using frameworks such as Flask or FastAPI.
  • Understanding of Docker Kubernetes Helm and Argo Workflows in production environments.
  • Understanding of CI/CD pipelines preferably using GitHub Actions or similar tools.
  • Proficiency in version control systems like Git/GitHub.
  • Hands-on experience working with cloud platforms such as Azure GCP or AWS.
  • Understanding of distributed computing frameworks like Spark and platforms like Azure Databricks or AWS EMR.

Soft Skills:

• • Excellent written and verbal communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
  • Proven problem-solving skills and a passion for debugging and troubleshooting complex issues.
  • Strong organizational skills with an ability to manage multiple tasks/projects simultaneously.

Nice to Have

• Solid understanding of the end-to-end ML lifecycle: data preparation feature engineering model training hyperparameter tuning model evaluation and deployment.
• Experience working with structured and unstructured data large-scale datasets and optimizing pipelines for performance and scalability.
• Ability to write modular testable and maintainable code for ML workflows.
• Domain knowledge in Supply Chain especially in Demand Planning CPG or Manufacturing industries.
• Understanding of how business drivers (e.g. pricing promotions seasonality weather patterns) influence demand.
• Experience working with time series forecasting or predictive modeling in operational contexts.
• Familiarity with MLFlow DVC or other ML experiment tracking and versioning tools.
• Exposure to ML model monitoring or model explainability frameworks.

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