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Full-Time

Lead Machine Learning Engineer

Confirmed live in the last 24 hours

Profitero

Profitero

201-500 employees

Empowers brands with digital shelf analytics

Consulting

Senior, Expert

Remote in USA

Category
Applied Machine Learning
Deep Learning
Natural Language Processing (NLP)
AI & Machine Learning
Required Skills
Microsoft Azure
Python NLTK
Python
Tensorflow
Keras
Pytorch
SQL
AWS
Pandas
Natural Language Processing (NLP)
NumPy
Google Cloud Platform
Requirements
  • Knowledge of Python (scipy, pandas, numpy, matplotlib, seaborn, plotly, etc.) + ML libraries (scikit-learn, xgboost, libffm, etc.)
  • Experience with MLOps tools and platforms (mlflow, dvc, GCP Vertex AI, Amazon Sagemaker, DataBricks, or other), knowledge of MLOps basics
  • Experience with designing, building, and deploying production applications and data pipelines
  • Experience automating MLOPs
  • Experience with CI/CD
  • Experience with cloud-native services: GCP, AWS, Azure
  • Knowledge of at least one of the Deep Learning frameworks: TensorFlow, Keras, PyTorch
  • Experience in Neural Networks training on text/image data. Understanding of working principles of different architectures (CNN, RNN, Transformers) for appropriate choice of Neural Network Architecture
  • Experience in NLP, starting from classic approaches to Neural Networks. Experience in the libraries like gensim, nltk, fasttext, etc.
  • Experience mentoring others in the area of expertise
  • Knowledge of SQL for basic queries
  • English B2
  • Problem-solving skills to develop quick yet sound solutions to resolve complex issues
  • Ability to work independently with attention to detail while performing tasks
  • Proactive, goal-oriented, and a good teammate
Responsibilities
  • Collaborate with data scientists and software engineers to build and improve ML models
  • Optimize and fine-tune ML models
  • Analyze data from multiple sources
  • Setup and analyze diverse metrics to measure the quality and effectiveness of ML models
  • Deliver ML models to production
  • Design, create, maintain, troubleshoot, and optimize the complete end-to-end machine learning life cycle
  • Analyze the business domain and suggest what data should be collected for future improvements
  • Create and maintain documentation for implemented solutions
  • Troubleshoot and resolve issues related to ML models in production scenarios
  • Provide capabilities for early detection of various drifts
  • Identify technical risks and gaps, devise mitigation strategies
  • Identify and eliminate technical debt in machine learning systems

Profitero offers intelligence-driven solutions for brands to optimize product positioning, pricing, and performance across 1200+ retailers in 70+ countries. Their integrated digital shelf analytics, shelf-intelligent activation, and advisory services empower brands to maximize conversions and leverage the Open Commerce Ecosystem for combining digital shelf data insights with other solutions.

Company Stage

M&A

Total Funding

$48.8M

Headquarters

Boston, Massachusetts

Founded

2010

Growth & Insights
Headcount

6 month growth

5%

1 year growth

1%

2 year growth

16%