Senior Machine Learning Engineer

Tel-Aviv
Technology – Data Science /
Full-time /
Hybrid
At Fairmatic we're on a mission to make roads safer, one fleet at a time. 

Fairmatic is revolutionizing the auto insurance industry by using data and AI to personalize options and incentivize safe driving with savings. Our predictive risk models have been trained with 200 billion miles of driving data and tested with hundreds of thousands of paying drivers.

Fairmatic's leadership team includes serial entrepreneurs, insurance industry innovators, and startup veterans who have raised over $88M in funding in less than a year.

Join our global team of curious, adaptable technologists and problem solvers who are passionate about creating a positive impact on the world!

We are looking for a talented and motivated Senior Machine Learning Engineer to join our Risk Intelligence team. Risk Intelligence is at the core of everything we do. You will help develop and productize machine learning models predicting claims frequency & severity and detecting fraud. You will help automate claims payouts and enhance other aspects of rating, claims, and the customer experience (e.g. insight to improve fleet safety). This role involves continuous experimentation, A/B testing, and an iterative approach to productizing our learnings. You will work closely with product management, data scientists and other product/engineering teams.

A day in life:

    • Understand business requirements, develop, train and operationalize models that cohesively integrate with the product and continuously benchmark their performance
    • Work alongside data scientists to develop new techniques, algorithms and systems to improve model performance and model training pipelines
    • Develop a platform that allows us to quickly and iteratively conduct experiments, and A/B testing to rapidly test, refine, deploy and productize new models
    • Develop APIs and ML libraries for easy integration with other services
    • Formulate and apply data quality standards and model verification protocols
    • Analyze data to identify patterns or anomalies that could affect model performance. Extract insights from data and explore potential improvements or developments
    • Contribute to and consistently raise the bar for engineering best practices including coding standards, writing well-tested code, extensible reusable libraries, and mentor junior engineers
    • Exemplify and foster Fairmatic’s humble, collaborative and impact-obsessed culture

What we need from you:

    • Bachelor’s degree in Computer Science Engineering or related field.
    • 3+ years experience as a Machine Learning Engineer, writing and maintaining production-grade ML systems that are designed to be performant, scalable and resilient.
    • 5+ years of experience with coding including ML years.
    • Hands-on experience designing, training, and deploying machine-learning models and building ML workflows.
    • Proven experience in working with ML libraries, such as scikit-learn, TensorFlow or PyTorch. 
    • Experience with data at scale using SQL, Pyspark, or similar frameworks.
    • Experience with cloud frameworks (like AWS sagemaker) and other MLOps tools for orchestration (like AirFLow) and experiment tracking (like MLFlow and weights & biases)
    • High proficiency in statistics and machine learning algorithms, data manipulation and analysis.
    • Excellent verbal/written communication skills
    • Self-driven and able to work independently on end-to-end projects
    • Comfortable working in a highly agile, intensely iterative software development process
Some of our Tel Aviv Office Benefits & Perks:
23 days of vacation
Payment for sick leave from day one
Keren Hishtalmut and Pension
Commuter and parking benefits
Hybrid working model
Mobile and home internet allowance
Team events, fully-stocked kitchen, happy hours
Stipends for wellness and entertainment
Awesome Fairmatic gifts and swag!

We are always on the hunt for talented individuals!

Join us and let’s fulfill our mission to make roads safer, one fleet at a time.