Senior Machine Learning Engineer
Confirmed on the employer's own hiring board on Oct 8, 2026. First seen by Alion on Aug 29, 2026.
Join BizAway, a fast-growing B2B scale-up, as a Senior Machine Learning Engineer. In this role, you will design, develop, and deploy ML-powered data products, collaborate with Data Analysts and Data Engineers, and own the full lifecycle of ML models. You will also contribute to defining best practices for ML development and promote a pragmatic approach to AI/ML within the company. Enjoy a full-time position with benefits including health insurance, employee welfare, a multicultural environment, remote work flexibility, and equity in the company.
Missions
- Designing, developing, and deploying ML-powered data products that enhance business value.
- Collaborating with Data Analysts and Data Engineers to ensure robust data pipelines and production-ready systems.
- Owning the full lifecycle of ML models, from problem framing and experimentation to deployment, monitoring, and continuous improvement.
Profil recherché
- If you like challenges and would love to be part of one of the fastest-growing B2B scale-ups, then BizAway is the company you have been looking for.- Ability to work independently and take ownership of projects end-to-end
- Familiarity with APIs and model serving (batch and/or real-time inference)
- Familiarity with Large Language Models and their use within end-to-end AI workflows
- Experience developing and deploying ML models in production environments
- Strong proficiency in Python and common ML libraries (e.g. scikit-learn, TensorFlow, PyTorch)
- Strong problem-solving skills and ability to translate business problems into ML solutions
- 5-8 years of experience in Machine Learning, Applied Data Science, or similar roles
- Solid understanding of core ML techniques (supervised and unsupervised learning)
- Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A PhD in a relevant discipline is a plus
- Experience with feature engineering and working with real-world datasets
- English proficiency (written and spoken, minimum B2 level)
- Experience with experimentation frameworks (A/B testing) and impact measurement
- Experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes)
- Knowledge of MLOps practices (model deployment, versioning, monitoring, retraining)