Machine Learning Engineer

Profitero is a leading global SaaS commerce platform that uses predictive intelligence to help brands anticipate, activate, and automate their next best action to fuel profitable growth. Our technology monitors 70 million products daily, across 700 retailers and 50 countries, helping brands optimize search placement, product content, pricing, stock availability, reviews, and more. News outlets, including Good Morning America, The Wall Street Journal, and Ad Age frequently cite and trust Profitero as a source of data for their stories.

Now’s an exciting time to join our fast-growing business.

Profitero has recently joined Publicis Groupe (a $13 billion global marketing services and technology company) as a standalone commerce division, infusing our business with significant product development resources and investment while giving our employees an incredible launchpad for their careers. Profitero’s tech and data combined with Publicis’ tech, data, and activation services position us to be a true end-to-end partner for helping brands maximize eCommerce market share and profits.

Come be a part of our fast-paced, entrepreneurial culture and next stage of growth.

We are inviting a ML Engineer to join our team.Our team is dedicated to developing, integrating, and enhancing ML solutions vital for Proftero’s client onboarding and product operations departments. As a key member, you’ll play a pivotal role in processing text data, automating branding, and categorizing millions of product entries. Your efforts will directly contribute to furnishing our clients with actionable insights drawn from our comprehensive data analysis.

Responsibilities:

• As a member of the Scrum Team collaborate with data scientists and software engineers to build new and improve existing ML models
• Optimize and fine-tune ML models to meet performance, efficiency, and accuracy goals
• Analyze data from multiple sources
• Setup and analyze diverse metrics to measure the quality and effectiveness of ML models used
• Deliver ML models to production, building scalable and cost-effective solutions
• 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 to make improvements in the future
• Create and maintain documentation for implemented solutions, ensuring accurate and concise reporting on technical specifications and system requirements
• Troubleshoot and resolve issues related to ML models usage in production scenarios, ensuring high reliability and performance
• Provide capabilities for early detection of various drifts (data, concept, schema, etc.)
• Continuously identify technical risks and gaps, devise mitigation strategies
• Identify and eliminate technical debt in machine learning systems

We expect:

• Knowledge of Python (scipy, pandas, numpy, matplotlib, seaborn, plotly, etc.) + ML libraries (scikit-learn, xgboost, libffm, etc.)
• Knowledge of major Machine Learning algorithms (both supervised and unsupervised). Choosing metrics, validation strategy, and appropriate models
• 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
• Last but not least: be proactive, goal-oriented and a good teammate
  
  

We provide:

• Working on the company’s own product, highly demanded worldwide, the industry leader in the e-commerce analytics segment
• Our vacancy implies a remote full-time work
• Vacation (20 working days per year, 100% paid)
• Health insurance reimbursement (up to 250 USD gross per year)
• Paid sick leave (80% of the daily base salary)
• 4 days for recovery without a sick leave document during the year (80% of the daily base salary)
• Individual sports activities reimbursement (50% of the check, up to 45 USD gross max per month)
• English classes reimbursement (100% of the check, up to 57 USD gross max per month)
• Professional development opportunities reimbursed by the company (seminars/training/conferences/etc.)
• Team-building activities