Job Summary
We’re looking for a versatile and motivated Machine Learning Engineer to join our AI and data science team. In this role, you’ll be responsible for developing, deploying, and maintaining ML models that power intelligent features and insights across our organization. You’ll collaborate with cross-functional teams to translate complex problems into scalable solutions that impact users and business outcomes.
This position is ideal for those passionate about machine learning systems—from hands-on implementation to designing architecture and leading ML strategy.
What You’ll Do
- Design, build, and deploy ML models for a variety of business and product use cases.
- Develop pipelines for training, inference, and monitoring across the model lifecycle.
- Conduct data preprocessing, feature engineering, and model evaluation.
- Collaborate with data scientists, product managers, and engineers to deliver ML solutions.
- Improve model performance, reliability, and scalability through experimentation and tuning.
- Contribute to the evolution of our ML platforms, tooling, and MLOps practices.
Experience Levels Accepted
We are hiring across all experience levels, from Intern to Head of Machine Learning:
| Seniority Level | Years of Experience | Expected Focus & Contribution |
| Intern | 0–1 years | Assist in ML experiments and learn applied machine learning workflows. |
| Junior | 1–3 years | Build and evaluate basic models; support training and deployment with guidance. |
| Mid-Level | 2–5 years | Own production models; build robust pipelines; collaborate across teams. |
| Senior | 4–8 years | Lead key ML projects; ensure reliability and performance; mentor junior engineers. |
| Lead | 7–12 years | Architect ML systems; lead strategic initiatives; standardize tools and practices. |
| Staff | 10–15 years | Set ML direction; lead innovation; shape company-wide ML strategy and infrastructure. |
| Head of Machine Learning | 15+ years | Define org vision; lead teams; align ML efforts with executive goals and company strategy. |
Note: Final title, compensation, and scope of responsibilities will be aligned with the candidate’s experience level and capabilities.
Tools & Technologies
- Python, R
- Scikit-learn, TensorFlow, PyTorch
- XGBoost, LightGBM, CatBoost
- MLflow, Weights & Biases
- Docker, Kubernetes
- AWS SageMaker, GCP Vertex AI, Azure ML
- Jupyter, Git
At Analytics 4 Retail, we are committed to building a diverse and inclusive workplace. We welcome applicants of all backgrounds and experiences, regardless of age, gender identity, sexual orientation, race, ethnicity, religion, disability status, or veteran status. We believe diverse perspectives drive innovation and better decision-making. We also value your privacy — all applications are treated with strict confidentiality and will be used solely for recruitment purposes in accordance with applicable data protection laws.
If you prefer not to fill out the online form or encounter any issues, you can also apply by sending your resume directly to careers@analytics4retail.com.
To apply for this job email your details to careers@analytics4retail.com