Job Title: Machine Learning Engineer - Montreal/Hybrid

Hey there! We're a trailblazing Travel Tech startup in Montreal, searching for a Machine Learning Engineer with a specialization in TABULAR PREDICTIONS and Large Language Models (LLMs). Join us to push the boundaries of predictive modeling and AI in travel technology, offering salaries between $120k and $200k based on expertise.

About Stay22

Stay22 is a fast growing and profitable startup that helps content creators to better monetize their content while improving the overall experience of their end users through different innovative solution that makes it easy to search for travel related services.

Why join Stay22 ?

We are dedicated to revolutionize the way we book travel, using ML & AI to develop new solutions to help content creators monetize their content.
Growing fast means growth opportunities.
We make our stars run their own show in the Stay22 universe.
We also have the coolest (and bright) lair, available if you want to mingle, in the center of Montreal’s Plateau Mont Royal, surrounded by the best shops and restaurants in town.
We take people as they are: come-as-you-are dress code, personalized work schedules…
We give them what they want: health & dental benefits, learning & development opportunities, social & team building activities including cool retreats…

Key Responsibilities:

Expertise in Machine Learning for TABULAR PREDICTIONS:

Strong background in machine learning, especially in developing forecasting and prediction models based on tabular data.
Proficient in Python and familiar with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) for model development and evaluation.
Experienced in data manipulation and visualization with tools like pandas, matplotlib, and seaborn to derive insights from data.
Skilled in using machine learning as a service platforms such as Google Vertex AI or Amazon SageMaker for model training, deployment, and management, emphasizing cost-efficiency and scalability.

Large Language Models:

Knowledge of Large Language Models (LLMs) and their application in generating insights and enhancing predictions via feature engineering
Experience with OpenAI's GPT and Google's Gemini and among other top LLMs, their pricing, tokenization difference, and other quirks.
Familiarity with prompt engineering and know when to instead do a fined-tuned version of the LLM.
Understands how to gather data for fined tuning in a scalable way
Bonus for creating and deploying custom LLMs, outlandish transformers or using custom embeddings and vectors

Data Science and Statistical Analysis:

Solid understanding of statistics and data analysis techniques.
Experience in handling, cleaning, and analyzing large datasets to derive actionable insights.
Ability to communicate complex data findings in a clear and effective manner.
Understands what makes our users tick, our north star metrics, and how to optimize towards that.

Autonomy and Innovation in ML Projects:

Demonstrated ability to lead ML projects from conception through deployment.
Self-starter with a track record of innovative problem solving and project management.
Openness to explore and implement the latest ML technologies and methodologies and ability to pick up and learn new things as we go

Cross-Disciplinary Collaboration:

Ability to work closely with engineering, product, and business teams to integrate ML solutions into the broader product ecosystem.
Strong communication skills and the capacity to translate technical concepts into business value.
Our stack is mostly in NodeJS and Python, so familiarity and ability to deploy, and monitor is key.

Requirements:

Relevant degree or equivalent experience in Machine Learning, Computer Science, or a related field.
Demonstrable projects or contributions applying ML

Mission:
Over 100 million unique users go every month through our script and map widget that is embedded in the top most pages and platforms in travel discovery. We are looking for someone who can sort through this data, experiment, fail, wake up, fail again, and then maybe fail one more time ;) This job is a trial and error. Sorting through our billions of row of data, finding patterns and anomolies. Have models evaluate against each other. Discover and engineer new features that the travel market hasn't thought about. If this is your jam, then we have the peanut n butter. Just bring the bread!