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AI/ML Engineer

sciemo

Salary not specified
Nov 12, 2025
New York, NY, US • Atlanta, GA, US • Philadelphia, PA, US • Raleigh-Durham, NC, US
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Sciemo builds AI for consumer goods, aiming to help businesses make faster, smarter, and more human decisions across the entire Sales and Operations Planning (S&OP) cycle by transforming messy, siloed data into measurable business impact.

Requirements

  • Experience with core ML/AI tools: Python, PyTorch, TensorFlow / Keras, scikit-learn, SQL, Spark.
  • Experience writing production-grade Python (object- and function-oriented).
  • Hands-on expertise with large-scale ML systems, GenAI (LLMs, diffusion), agents, and graph-based models.
  • Experience designing and managing ML orchestration workflows and versioned pipelines (Airflow, ZenML, Kedro, dbt, etc.).
  • Proven track record of launching AI/ML products into production.

Responsibilities

  • Architect, build, and deploy ML/GenAI products on cloud infrastructure (AWS or similar).
  • Design and implement end-to-end AI workflows: data ingestion, feature engineering, modeling, evaluation, and deployment.
  • Create automated pipelines for continuous learning, model promotion, and performance monitoring.
  • Lead the design of ML orchestration frameworks (Airflow, Kedro, ZenML, Flyte) to ensure reproducibility and scalability.
  • Oversee deployment of large-scale and multi-agent AI systems with high reliability and fault tolerance.
  • Continuously optimize workflows for efficiency, robustness, and performance in production.
  • Translate complex business problems into AI solutions, including data collection, experiment design, and roadmap planning.

Other

  • As one of the earliest technical hires, you will help define our AI strategy, set technical standards, and establish best practices for applied AI at scale.
  • Work directly with customers and stakeholders to ensure deployed systems achieve their intended impact.
  • Stay current with advancements in AI/ML, including LLMs, diffusion models, graph AI, and agent architectures.
  • Propose and prototype new approaches for integrating emerging technologies into production products.
  • Develop methods to quantify and communicate AI performance and business ROI.