Senior/ Staff ML Engineer - Recommendations Systems
The Opportunity:
We are looking for a machine learning engineer who has worked in search and personalization and is scrappy and pragmatic, using data and deductive reasoning to apply practical approaches into their algorithms. They’ll work directly with our VP of Data to create a search algorithm that improves the matching experience between clients and providers, with potential to bring Machine Learning to other surfaces across the company.
What You’ll Be Doing:
Design, develop, and deploy a scalable search ranking algorithm to enhance and personalize user experience on the Grow Therapy platform.
Collaborate with data scientists to define and extract relevant features from large datasets.
Implement machine learning models for search ranking, including training, evaluation, and optimization.
Develop and maintain data pipelines and infrastructure to support the continuous improvement of the search algorithm.
A/B testing design and analysis of performance differences between existing and new model variations to ensure confidence in positive business outcome improvements.
You’ll Be a Good Fit if you have:
Experience building and deploying machine learning models in the context of search ranking or recommendation systems.
5+ years of experience as a ML engineer or Data Scientist- ideally at an early stage or high growth startup - specializing in machine learning algorithms
Past experience building algorithms from 0->1 and an entrepreneurial mindset
Strong programming skills in Python and SQL.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
Proficiency in working with large datasets, data preprocessing, and feature engineering.
Knowledge of information retrieval, natural language processing, and ranking algorithms.
Ability to work cross functionally with growth, engineering, product, and an executive team
Knowledge and experience in best practices in applying MLOps in an organization with an emphasis on continuous development and deployment.
Role Details:
Employment Type: Full Time, Exempt
Base Compensation: The base compensation range for this position is
Hybrid Commitment: $218,000 - $269,000 USD annually
Fully Remote Commitment: $207,000 - $255,000 USD annually This role can be hybrid (onsite from our NYC, San Francisco, or Seattle hub location three days per week: Tuesday, Wednesday, Thursday) or fully remote. Both arrangements include travel 2–3 times per year (e.g., company and department offsites).
The base compensation for this role will vary depending on several factors, including relevant experience, qualifications, and the candidate's working location.
About the job
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Senior/ Staff ML Engineer - Recommendations Systems
The Opportunity:
We are looking for a machine learning engineer who has worked in search and personalization and is scrappy and pragmatic, using data and deductive reasoning to apply practical approaches into their algorithms. They’ll work directly with our VP of Data to create a search algorithm that improves the matching experience between clients and providers, with potential to bring Machine Learning to other surfaces across the company.
What You’ll Be Doing:
Design, develop, and deploy a scalable search ranking algorithm to enhance and personalize user experience on the Grow Therapy platform.
Collaborate with data scientists to define and extract relevant features from large datasets.
Implement machine learning models for search ranking, including training, evaluation, and optimization.
Develop and maintain data pipelines and infrastructure to support the continuous improvement of the search algorithm.
A/B testing design and analysis of performance differences between existing and new model variations to ensure confidence in positive business outcome improvements.
You’ll Be a Good Fit if you have:
Experience building and deploying machine learning models in the context of search ranking or recommendation systems.
5+ years of experience as a ML engineer or Data Scientist- ideally at an early stage or high growth startup - specializing in machine learning algorithms
Past experience building algorithms from 0->1 and an entrepreneurial mindset
Strong programming skills in Python and SQL.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
Proficiency in working with large datasets, data preprocessing, and feature engineering.
Knowledge of information retrieval, natural language processing, and ranking algorithms.
Ability to work cross functionally with growth, engineering, product, and an executive team
Knowledge and experience in best practices in applying MLOps in an organization with an emphasis on continuous development and deployment.
Role Details:
Employment Type: Full Time, Exempt
Base Compensation: The base compensation range for this position is
Hybrid Commitment: $218,000 - $269,000 USD annually
Fully Remote Commitment: $207,000 - $255,000 USD annually This role can be hybrid (onsite from our NYC, San Francisco, or Seattle hub location three days per week: Tuesday, Wednesday, Thursday) or fully remote. Both arrangements include travel 2–3 times per year (e.g., company and department offsites).
The base compensation for this role will vary depending on several factors, including relevant experience, qualifications, and the candidate's working location.