Brillio

Senior Lead AI/ML Engineer

Brillio

full-time

Posted on:

Location Type: Hybrid

Location: Chicago • Illinois • 🇺🇸 United States

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Job Level

Senior

Tech Stack

AirflowAWSAzureCloudDockerFlaskGoogle Cloud PlatformKafkaPandasPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

  • Partner with product and business teams to define problems and translate them into data-driven solutions.
  • Conduct exploratory data analysis (EDA) and extract actionable insights from structured and unstructured datasets.
  • Develop, validate, and iterate on predictive models using techniques in supervised, unsupervised, and/or time series learning.
  • Communicate modeling outcomes through clear visualizations and presentations to both technical and non-technical stakeholders.
  • Build and maintain robust pipelines for model training, evaluation, and inference.
  • Deploy machine learning models into production with attention to scalability, performance, and observability.
  • Monitor model drift and performance over time and develop retraining and versioning strategies.
  • Collaborate with software and data engineering teams to integrate ML solutions into end-user applications and internal systems.

Requirements

  • Master’s plus degree in Computer Science, Statistics, Applied Mathematics, or a related field.
  • 5+ years of experience in data science and machine learning, with a proven track record of delivering models to production.
  • Proficiency in Python and ML libraries such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow.
  • Strong understanding of statistical modeling, machine learning algorithms, and experiment design.
  • Solid experience with SQL and data manipulation tools (e.g., Pandas, Spark, or Dask).
  • Experience deploying models using APIs (Flask, FastAPI), Docker, and orchestration tools (e.g., Airflow, Kubeflow, MLflow).
  • Hands-on experience with cloud platforms (AWS, GCP, or Azure) and model serving tools.
  • Excellent problem-solving and communication skills; able to explain complex concepts clearly and effectively.
  • Experience with time series forecasting, causal inference, recommendation systems, or NLP (preferred).
  • Familiarity with data versioning and reproducibility tools (e.g., DVC, Weights & Biases) (preferred).
  • Exposure to feature stores, streaming data (e.g., Kafka), or real-time ML systems (preferred).
  • Background in MLOps and experience building generalizable ML frameworks or platforms (preferred).

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
data sciencemachine learningpredictive modelingexploratory data analysisstatistical modelingtime series learningSQLPythondata manipulationNLP
Soft skills
problem-solvingcommunicationcollaborationpresentationvisualization
Certifications
Master’s degree in Computer ScienceMaster’s degree in StatisticsMaster’s degree in Applied Mathematics

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