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Niche · 2 hours ago

Staff Machine Learning Engineer

United States

Full-time

Remote

Lead/Staff

$178K/yr - $222K/yr

8+ years exp

Niche is the leader in school search, aiming to simplify the process of researching and enrolling in schools. They are seeking a Staff Machine Learning Engineer to lead their machine learning initiatives, responsible for developing and deploying models that enhance user experience and drive business growth.

E-LearningEducationInternetService Industry

Comp. & Benefits

No H1B

Responsibilities

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

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

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

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

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

Qualification

Machine LearningPythonMLOpsSQLCloud PlatformsData ProcessingBusiness AcumenLeadershipCommunicationCollaboration

Required

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

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

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

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

Experience or a strong aptitude for leading technical projects, defining technical direction, and mentoring others. Excellent communication and collaboration skills

MS or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field, OR equivalent practical experience demonstrating deep expertise in machine learning