Niche
Overview
About Niche: Niche is the leader in school search. Our mission is to make researching and enrolling in schools easy, transparent, and free. We provide in-depth profiles, reviews and ratings, and search tools to help millions of people find the right school. We help schools recruit more best-fit students by highlighting what makes them great and facilitating visits and applications. About The Role: We are looking for our first Staff Machine Learning Engineer to establish and lead our machine learning initiatives. This is a foundational role where you will shape the future of data science and ML at Niche. You will identify high-impact opportunities, design, build, deploy, and monitor machine learning models that drive business growth and enhance user experience across our platform. You are a hands-on practitioner who translates business challenges into data-driven solutions and ships measurable results. You will mentor future ML hires and establish best practices as our capabilities grow. What You Will Do
Identify & Prioritize: Collaborate with product, engineering, data analytics, and business stakeholders to identify and prioritize impactful ML opportunities aligned with Niche's goals. Our first area of focus is Recommendations to match students with the right schools. Design & Build: Lead end-to-end development of ML models—from data collection and feature engineering to algorithm selection, training, tuning, and validation. This is a hands-on coding role. Deploy & Integrate: Develop production-grade code and systems to deploy, serve, and monitor ML models at scale, ensuring reliability and performance. Integrate models into Niche’s products and internal systems. Measure & Iterate: Define KPIs, establish monitoring, analyze model performance in production, and drive continuous improvement through experimentation. Champion & Evangelize: Communicate complex ML concepts and results to technical and non-technical audiences. Promote ML and data science across the organization. Lead & Mentor: Establish ML development best practices, coding standards, and documentation. Guide and mentor other ML engineers as the function grows. Innovate: Stay current with ML, data science, and MLOps trends and evaluate new technologies relevant to Niche. Path to Impact
First Month: Learn about Niche, platform, data architecture, and onboarding; align with teams on ML impact areas; begin shaping an ML roadmap. Within 3 Months: Deploy your first production ML model with monitoring; define success metrics and integration strategies; establish early ML workflows and documentation; contribute production-ready code. Within 6 Months: Improve through experimentation; introduce scalable MLOps; mentor and establish engineering best practices for the ML function. Within 12 Months: Lead ML efforts across multiple product areas; influence company strategy through technical leadership; develop internal tooling and reusable frameworks; help grow the team through hiring and mentorship. What We Are Looking For
Experience: 8+ years in software development or data science with at least 5+ years deploying ML models in production. Proven Impact: Track record of shipping ML models that drove measurable business growth (e.g., increased user engagement, conversions, efficiency, revenue). Technical Depth (Hands-On): Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, Keras, XGBoost); strong ML theory (classification, regression, clustering, recommendation, NLP, time series); strong SQL; ML deployment and MLOps concepts; cloud familiarity (AWS, GCP, Azure). Business Acumen: Ability to translate business needs into well-defined ML problems and tie technical work to strategic objectives. Leadership: Experience or aptitude for leading technical projects, setting direction, mentoring others, and strong communication. Education: MS or PhD in Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience. Bonus Points
Experience building ML capabilities from the ground up; recommendations, search ranking, or NLP for user-generated content. EdTech or consumer-facing platform experience. Familiarity with Go, Express, Postgres, Snowflake, DBT, Tableau. Contributions to open-source ML projects or publications. Compensation
Our national target base salary range is $152,320-$215,000, plus participation in our Annual Bonus and Stock Option Program. Base compensation will be commensurate with experience and skills. Total Rewards Philosophy focuses on performance-based compensation, best-in-class benefits, work-life balance, and employee well-being. Interview Process
We provide a transparent interview process where you learn about us and we share our expectations. The process is outlined here: Phone Screen with Talent Acquisition Partner – 30 Minutes Video Interview with Hiring Manager – 45 Minutes Case Study, Presentation, and System Design Team Interview – 45 Minutes Leadership Interview – 30 Minutes Why Niche?
Flexible work options (remote, Pittsburgh office, or hybrid). Full-time, salaried position with competitive compensation. Best-in-class health plan with vision and dental. Flexible Paid Time Off; home office stipend. Parental leave (12 weeks fully paid) plus disability coverage for birthing parents. 401(k) with employer match. Opportunity to make an immediate impact and work with a team that cares. Niche will only employ those legally authorized to work in the United States without sponsorship for this opening. We are hiring in the following states: AZ, CO, CT, DE, FL, GA, IL, IN, KY, LA, ME, MD, MA, MI, MO, NE, NV, NH, NJ, NY, NC, OH, OK, OR, PA, SC, TN, TX, VA, WA, DC, WV. Candidates only. No recruiters or agencies. Relocation assistance is not offered. Niche is an equal opportunity employer committed to an inclusive, innovative environment with employment opportunities without regard to age, race, color, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. All interviews are conducted remotely. If we can make preparations to improve your interview experience, please let us know.
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About Niche: Niche is the leader in school search. Our mission is to make researching and enrolling in schools easy, transparent, and free. We provide in-depth profiles, reviews and ratings, and search tools to help millions of people find the right school. We help schools recruit more best-fit students by highlighting what makes them great and facilitating visits and applications. About The Role: We are looking for our first Staff Machine Learning Engineer to establish and lead our machine learning initiatives. This is a foundational role where you will shape the future of data science and ML at Niche. You will identify high-impact opportunities, design, build, deploy, and monitor machine learning models that drive business growth and enhance user experience across our platform. You are a hands-on practitioner who translates business challenges into data-driven solutions and ships measurable results. You will mentor future ML hires and establish best practices as our capabilities grow. What You Will Do
Identify & Prioritize: Collaborate with product, engineering, data analytics, and business stakeholders to identify and prioritize impactful ML opportunities aligned with Niche's goals. Our first area of focus is Recommendations to match students with the right schools. Design & Build: Lead end-to-end development of ML models—from data collection and feature engineering to algorithm selection, training, tuning, and validation. This is a hands-on coding role. Deploy & Integrate: Develop production-grade code and systems to deploy, serve, and monitor ML models at scale, ensuring reliability and performance. Integrate models into Niche’s products and internal systems. Measure & Iterate: Define KPIs, establish monitoring, analyze model performance in production, and drive continuous improvement through experimentation. Champion & Evangelize: Communicate complex ML concepts and results to technical and non-technical audiences. Promote ML and data science across the organization. Lead & Mentor: Establish ML development best practices, coding standards, and documentation. Guide and mentor other ML engineers as the function grows. Innovate: Stay current with ML, data science, and MLOps trends and evaluate new technologies relevant to Niche. Path to Impact
First Month: Learn about Niche, platform, data architecture, and onboarding; align with teams on ML impact areas; begin shaping an ML roadmap. Within 3 Months: Deploy your first production ML model with monitoring; define success metrics and integration strategies; establish early ML workflows and documentation; contribute production-ready code. Within 6 Months: Improve through experimentation; introduce scalable MLOps; mentor and establish engineering best practices for the ML function. Within 12 Months: Lead ML efforts across multiple product areas; influence company strategy through technical leadership; develop internal tooling and reusable frameworks; help grow the team through hiring and mentorship. What We Are Looking For
Experience: 8+ years in software development or data science with at least 5+ years deploying ML models in production. Proven Impact: Track record of shipping ML models that drove measurable business growth (e.g., increased user engagement, conversions, efficiency, revenue). Technical Depth (Hands-On): Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, Keras, XGBoost); strong ML theory (classification, regression, clustering, recommendation, NLP, time series); strong SQL; ML deployment and MLOps concepts; cloud familiarity (AWS, GCP, Azure). Business Acumen: Ability to translate business needs into well-defined ML problems and tie technical work to strategic objectives. Leadership: Experience or aptitude for leading technical projects, setting direction, mentoring others, and strong communication. Education: MS or PhD in Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience. Bonus Points
Experience building ML capabilities from the ground up; recommendations, search ranking, or NLP for user-generated content. EdTech or consumer-facing platform experience. Familiarity with Go, Express, Postgres, Snowflake, DBT, Tableau. Contributions to open-source ML projects or publications. Compensation
Our national target base salary range is $152,320-$215,000, plus participation in our Annual Bonus and Stock Option Program. Base compensation will be commensurate with experience and skills. Total Rewards Philosophy focuses on performance-based compensation, best-in-class benefits, work-life balance, and employee well-being. Interview Process
We provide a transparent interview process where you learn about us and we share our expectations. The process is outlined here: Phone Screen with Talent Acquisition Partner – 30 Minutes Video Interview with Hiring Manager – 45 Minutes Case Study, Presentation, and System Design Team Interview – 45 Minutes Leadership Interview – 30 Minutes Why Niche?
Flexible work options (remote, Pittsburgh office, or hybrid). Full-time, salaried position with competitive compensation. Best-in-class health plan with vision and dental. Flexible Paid Time Off; home office stipend. Parental leave (12 weeks fully paid) plus disability coverage for birthing parents. 401(k) with employer match. Opportunity to make an immediate impact and work with a team that cares. Niche will only employ those legally authorized to work in the United States without sponsorship for this opening. We are hiring in the following states: AZ, CO, CT, DE, FL, GA, IL, IN, KY, LA, ME, MD, MA, MI, MO, NE, NV, NH, NJ, NY, NC, OH, OK, OR, PA, SC, TN, TX, VA, WA, DC, WV. Candidates only. No recruiters or agencies. Relocation assistance is not offered. Niche is an equal opportunity employer committed to an inclusive, innovative environment with employment opportunities without regard to age, race, color, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. All interviews are conducted remotely. If we can make preparations to improve your interview experience, please let us know.
#J-18808-Ljbffr