Who are we:
The restaurant industry generates vast amounts of data, presenting a unique opportunity for intelligent solutions. At SynergySuite, we’re harnessing this potential to build powerful AI and Machine Learning driven features that provide actionable insights and automation for our clients. We’re a leading SaaS provider committed to simplifying complexity and empowering restaurant owners and operators to make data-driven decisions. We’re now seeking a skilled AI Engineer with a strong background in Machine Learning to join our team and help us unlock even greater value from this data, driving innovation and tangible results for our customers.
Our robust and scalable platform is built on AWS, utilizing a modern microservices architecture, RESTful APIs, and advanced services like SageMaker Studio for our AI/ML initiatives.
Who you are:
Beyond your technical expertise, you are a highly collaborative team player who thrives on shared success. You possess an insatiable curiosity and a genuine passion for learning and experimenting with the latest advancements in AI and Machine Learning. You are comfortable navigating projects where requirements may not always be crystal clear, demonstrating your adaptability and proactive approach to problem-solving. You are an excellent communicator, able to articulate complex ideas effectively, and you value a supportive and intellectually stimulating work environment.
The Role:
- Design, develop, and implement machine learning models and algorithms to address specific business needs within the restaurant management domain (e.g., forecasting demand, optimizing inventory, personalizing recommendations, detecting anomalies).
- Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
- Deploy and monitor machine learning models in production environments, ensuring performance, reliability, and scalability.
- Contribute to the development of the AI/ML roadmap and identify opportunities for innovation.
- Continuously evaluate and improve existing machine learning models through experimentation, retraining, and the application of new techniques.
- Collaborate effectively with product managers, software engineers, and other stakeholders to understand business requirements and translate them into technical solutions.
- Stay up-to-date with the latest advancements in AI and Machine Learning, evaluating their potential application to SynergySuite’s products and services.
- Research and experiment with new algorithms, techniques, and tools to improve model performance and explore novel solutions.
- Communicate complex technical concepts clearly and concisely to both technical and non-technical audiences.
- Leadership and Mentorship: This role offers the opportunity to take on a leadership position by mentoring and guiding junior AI engineers. You will be instrumental in fostering a collaborative learning environment where knowledge is shared, and everyone has the opportunity to grow. You will help cultivate their technical skills, build their confidence, and contribute to their professional development within SynergySuite.
Requirements:
- 3+ years of professional experience with data analysis and data science.
- Strong programming ability with SQL, Python, Pandas, Numpy, Scikit-learn
- Experience with TSA (Time Series Analysis), such as
- Understanding of autocorrelation, stationarity, classical TSA algorithms (e.g. exponential smoothing)
- Understanding the effect that different error metrics have on the optimal fitting of a forecast
- Understanding modern statistical methods for TSA (e.g. state space models) or deep learning methods
- Experience with end-to-end development of a production-level forecasting pipeline
- Basic experience with MLOps and orchestration
- Experience with Programming Notebooks
- Good communication and explanation skills
Nice to Have
- Experience with data engineering
- Experience with AWS Sagemaker Studio
- Experience working with LLMs
- Degree in statistics, mathematics, or closely related field
- Experience maintaining data science models and monitoring performance and drift
