Summary
About this role
We are seeking a Machine Learning / AI Engineer who bridges data engineering and front-end systems. The ideal candidate is skilled in structuring data pipelines, training ML models, and integrating outputs into interactive user interfaces.
Key Responsibilities:
• Design and implement ML/AI models for real-time decision-making.
• Collaborate with data engineers to prepare and structure large-scale datasets.
• Integrate ML results into front-end applications for visualization and interaction.
• Deploy, monitor, and optimize ML models in production.
• Work with cross-functional teams to define data-driven product strategies.
• Ensure reproducibility, version control, and thorough documentation of ML workflows.
Skills and Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field.
• 3+ years of experience in machine learning or data engineering.
• Strong experience with Agentic Frameworks like LangGraph, Crew AI, and Llama Index, important for this client’s agentic application.
• Proficient in Python and data manipulation libraries (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch).
• Experience with AWS services and Lambda-based deployments.
• Familiarity with front-end data visualization or React integration is a strong plus.
• Excellent English communication and collaboration skills; C1 English Level.
\nOther facts
About Distro
About Distro
Distro is the AI co-pilot for counter staff and inside sales at industrial wholesale distributors.
About Distro
Distro is the AI Revenue Platform for sales reps in the industrial distribution industry. Our platform helps reps quote faster, close more business, and improve margins, all while delivering a superior customer experience. We’re a well-funded, venture-backed and Y Combinator-backed (S24) startup with strong traction and growing customer demand. Our goal is to modernize a massive industry that has historically been underserved by software.
What you'll do
- The role involves designing and implementing ML/AI models for real-time decision-making and collaborating with data engineers to prepare large-scale datasets. Additionally, the specialist will integrate ML results into front-end applications and ensure the optimization of models in production.
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