Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Improving existing ML library & tools allowing to explore and analyze more and more data and provide accurate feedback on the hirify.global activities with an accent on robustness, performance, and scalability. Focus on implementing ML models and algorithms, particularly in production environments.

Location: Hybrid work (3 days per week in the office)

Company

hirify.global is a leading omnichannel advertising platform focused on driving outcomes for brand and performance advertisers across screens.

What you will do

• Improve existing ML library & tools allowing to explore and analyze more and more data and provide accurate feedback on the hirify.global activities.
• Create, design, develop, test and monitor your code in production autonomously and reliably.
• Design, develop, and implement ML models and algorithms with a focus on robustness, performance, and scalability.
• Collaborate with data scientists to identify and apply effective machine learning techniques and strategies for improved system performance.
• Mentor other team members to improve their autonomy and Software Engineering skills.
• Collaborate with variety of teams for production cases to develop services from design to production.

Requirements

• Strong programming skills with a focus on Python, Java, Scala and proficiency in software engineering practices such as testing, debugging, and performance tuning.
• Hands-on experience implementing machine learning algorithms, particularly in production environments.
• Strong problem solving skills.
• Strong communication skills, with the ability to collaborate effectively across teams and explain complex technical concepts clearly.

Nice to have

• Knowledge of Data Engineering tools (e.g. Spark, Airflow, ...).
• Familiarity with ML frameworks and tools (e.g., TensorFlow, PyTorch,..).
• Performance engineering capabilities, including profiling and optimizing algorithms and systems for high efficiency and low latency.
• Experience working with cloud-based infrastructures (e.g., AWS, GCP).
• A Master’s or PhD in SC/Math.

Culture & Benefits

• Career Development: Continuous investment in our employees’ skills: in-house and external training, internal mobility …
• Life Balance: A well-balanced work-life for our employees is one of our top priorities: 22 days off per year, hybrid work (3 days per week in the office)
• Wellness: Prioritizing employee well-being through premium work equipment, enjoyable work environment (work-life balance, team building events, summits), remote work subsidy, promoting Diversity & Inclusion with internal & external initiatives, etc.