Staff Machine Learning Engineer at Niche

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Full Time

Start Date

Immediate

Expiry Date

26 Dec, 25

Salary

215000.0

Posted On

27 Sep, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Python, SQL, MLOps, Cloud Platforms, Feature Engineering, Model Deployment, NLP, Recommendation Systems, Data Processing, Experimentation, Model Evaluation, Mentoring, Technical Leadership, Collaboration

Industry

technology;Information and Internet

Description

About Niche Niche is the leader in school search. Our mission is to make researching and enrolling in schools easy, transparent, and free. With in-depth profiles on every school and college in America, 140 million reviews and ratings, and powerful search tools, we help millions of people find the right school for them. We also help thousands of schools recruit more best-fit students, by highlighting what makes them great and making it easier to visit and apply. Niche is all about finding where you belong, and that mission inspires how we operate every day. We want Niche to be a place where people truly enjoy working and can thrive professionally. About The Role We are looking for our first Staff Machine Learning Engineer to establish and lead our machine learning initiatives. This is a critical, foundational role where you will have the unique opportunity to shape the future of data science and ML at Niche. You will be responsible for identifying high-impact opportunities, designing, building, and deploying machine learning models that directly drive business growth and enhance user experience across our platform. We are looking for a highly skilled, hands-on practitioner who is passionate about translating business challenges into data-driven solutions. You aren't just theoretical; you build, you code, you ship, and you measure. You have a proven history of deploying ML models into production environments that have delivered tangible results. You possess the experience and desire to mentor future ML hires and establish best practices as our capabilities grow. What You Will Do Identify & Prioritize: Collaborate closely with product, engineering, data analytics, and business stakeholders to identify and prioritize the most impactful ML opportunities that align with Niche's strategic goals. Our first area of focus is our Recommendations, which includes matching students with the right schools Design & Build: Lead the end-to-end development of machine learning 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 effectively into Niche’s products and internal systems Measure & Iterate: Define key performance metrics, establish robust monitoring frameworks, analyze model performance in production, and drive continuous improvement through iteration and experimentation Champion & Evangelize: Clearly communicate complex ML concepts, model behaviors, and results to both technical and non-technical audiences. Champion the use of machine learning & data science across the organization Lead & Mentor: Establish ML development best practices, coding standards, and documentation. As the function grows you will guide and mentor other ML engineers Innovate: Stay abreast of the latest advancements in machine learning, data science, and MLOps, evaluating and potentially adopting new technologies and techniques relevant to Niche During the First Month: Learn about Niche by meeting with various team members to learn more about our company through our Onboarding meetings Deep-dive into Niche’s platform, data architecture, and recommendation systems Align with product and engineering teams on business goals and ML impact areas Begin shaping a roadmap for high-impact ML opportunities Within 3 Months: Deploy your first machine learning model into production with robust monitoring and feedback loops Collaborate with product and engineering to define success metrics and integration strategies Establish early ML development workflows, documentation, and performance monitoring Contribute production-ready code for feature engineering and model experimentation Within 6 Months: Drive measurable improvements through experimentation and model iteration Introduce scalable MLOps practices to support deployment, retraining, and governance Serve as a mentor and set engineering best practices for a growing ML function Within 12 Months: Lead ML efforts across multiple product areas, driving business impact at scale Influence company-wide strategy through technical leadership and ML evangelism Develop internal tooling, reusable frameworks, and scalable ML systems Help grow the team through hiring, mentorship, and a culture of innovation What We Are Looking For Experience: 8+ years of professional experience in software development or data science, with at least 5+ years specifically focused on building and deploying machine learning models in a production environment Proven Impact: Demonstrable track record of successfully shipping multiple machine learning models that resulted in measurable business growth (e.g., increased user engagement, conversion rates, operational efficiency, revenue). You can clearly articulate the business problem, the ML solution, and the quantitative impact achieved Technical Depth (Hands-On): Expertise in Python and common ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Keras, XGBoost) Deep understanding of core ML concepts (e.g., classification, regression, clustering, recommendation systems, NLP, time series analysis, experimentation, model evaluation) Strong SQL skills and experience working with large datasets and data processing tools (e.g., Pandas, Spark) Experience with ML deployment patterns and MLOps principles (e.g., model serving, monitoring, CI/CD for ML, feature stores) Familiarity with cloud platforms (AWS, GCP, Azure) is essential Business Acumen: Strong ability to understand business needs, translate them into well-defined ML problems, and connect technical work back to strategic objectives. You prioritize work based on potential business impact Leadership Experience: Experience or a strong aptitude for leading technical projects, defining technical direction, and mentoring others. Excellent communication and collaboration skills Education: MS or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, OR equivalent practical experience demonstrating deep expertise in machine learning Bonus Points Experience building ML capabilities from the ground up Experience with recommendation systems, search ranking algorithms, or NLP applied to user-generated content Experience in the EdTech or consumer-facing platform space Familiarity with golang, express, Postgres, Snowflake, DBT, and Tableau Contributions to open-source ML projects or publications in relevant conferences/journals 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. At Niche, our Total Rewards Philosophy is centered around creating a workplace environment that attracts, motivates, and retains top talent by providing a comprehensive and competitive rewards package. This philosophy is built on the principles of performance-based compensation, best-in-class benefits and work-life balance, and employee well-being. Interview Process Candidate experience is a top priority for our talent and hiring teams. We believe in providing a transparent, authentic and comprehensive interview process where you have the opportunity to learn about us while we get to know you and your experience. The interview 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? We are a fully flexible workforce empowering our employees to choose to work remotely, in our Pittsburgh office or whatever combination suits you Full time, salaried position with competitive compensation in a fast-growing company Best-in-class 100% paid employee health plan, including vision and dental and supplemental coverage Flexible Paid Time Off Policy Stipend that allows you to build your work from home office in a style and function that suits your personal preferences Parental leave for all employees (12 weeks fully paid) in addition to short term disability for birthing parents Meaningful 401(k) with employer match Your ideas and work will make an immediate impact on our company and millions of users You will join a team that cares about you, our mission, our work - and celebrates our wins together! Niche will only employ those who are legally authorized to work in the United States without sponsorship now or in the future for this opening. We are currently hiring in states where we currently have employees: 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, please. Sorry, we do not offer relocation assistance. Niche is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. Therefore, we provide employment opportunities without regard to age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. All interviews are being held remotely. If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

Responsibilities

The Staff Machine Learning Engineer will identify high-impact opportunities and lead the development of machine learning models to drive business growth. This role involves collaborating with various stakeholders and ensuring the integration of ML models into Niche’s products.