Senior Machine Learning Engineer

About BizAway

Here at BizAway, we Deliver the Future of Travel. 😎

We are a solid international company with strong ambitions and great expertise. With a focus on sustainability 🌱, on a daily basis we support companies enabling them to improve their travel management through our constantly evolving services and solutions, always characterized by our tech attitude and smart and innovative processes. 🚀

We know that success comes from People and deserves to be recognized.👫Proactivity and Reliability, Kind collaboration, and communication are the core values of our Solution Culture.

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. 🤩
 

We are looking for
 

We are looking for a driven and enthusiastic Senior Machine Learning Engineer (m/w/d) , who desires to contribute to the growth and success of our Data & Analytics Team.

Your role in BizAway
 

• As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying ML-powered data products that enhance our value proposition and drive business impact.
• You will collaborate closely with Data Analysts to translate business needs and KPIs into modeling approaches, and with Data Engineers to ensure robust data pipelines, feature availability, and production-ready systems.
• You will own the full lifecycle of ML models, from problem framing and experimentation to deployment, monitoring, and continuous improvement, ensuring that models deliver measurable value over time.
• You will contribute to defining best practices for ML development, including model evaluation, versioning, and performance monitoring, while promoting a pragmatic and impact-driven approach to AI/ML within the company.

Your basic qualifications
 

• 5-8 years of experience in Machine Learning, Applied Data Science, or similar roles
• Strong proficiency in Python and common ML libraries (e.g. scikit-learn, TensorFlow, PyTorch)
• Experience developing and deploying ML models in production environments
• Solid understanding of core ML techniques (supervised and unsupervised learning)
• Experience with feature engineering and working with real-world datasets
• 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
• Strong problem-solving skills and ability to translate business problems into ML solutions
• Ability to work independently and take ownership of projects end-to-end
• Master’s degree in Computer Science, Engineering, Mathematics, or a related field. A PhD in a relevant discipline is a plus.
• English proficiency (written and spoken, minimum B2 level)

We are also interested in 
 

• 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)

Our offer

📄 Contract type: Permanent 
🕓 Working hours: Full-time – 40h/week, from Monday to Friday
🏢 Hybrid (Barcelona): We love the focus of remote work, but we also value the magic of high-bandwidth, in-person collaboration. You can work from home most of the time, but we
expect you to swing by our Barcelona office a couple of times a week to brainstorm, whiteboard UX flows, and grab a coffee with the team.
💰 Salary:  Attractive compensation, including equity in the company
💼 Equity in the company (stock options plan)
✈️ A seat on a scale-up with skyrocketing growth
📈 Development of your entrepreneurial spirit, having the chance to implement real-impact business decision
🌍Multicultural and international team
🙌Collaborative and smart environment to work and learn
🍻Free coffee to kick-start your day and free beers to celebrate together


BizAway avoids any discrimination based on age, gender, sexual orientation, health status, nationality, political opinions, and religious beliefs in all decisions affecting personnel selection.