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Niche · 2 months ago

Copy of 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 make researching and enrolling in schools easy and transparent. The Staff Machine Learning Engineer will establish and lead machine learning initiatives, focusing on identifying opportunities, designing models, and deploying them to enhance user experience and drive business growth.

E-LearningEducationInternetService Industry

Comp. & Benefits

No H1B

Responsibilities

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

Lead the end-to-end development of machine learning models – from data collection and feature engineering to algorithm selection, training, tuning, and validation

Develop production-grade code and systems to deploy, serve, and monitor ML models at scale, ensuring reliability and performance

Define key performance metrics, establish robust monitoring frameworks, analyze model performance in production, and drive continuous improvement through iteration and experimentation

Clearly communicate complex ML concepts, model behaviors, and results to both technical and non-technical audiences

Establish ML development best practices, coding standards, and documentation

Stay abreast of the latest advancements in machine learning, data science, and MLOps, evaluating and potentially adopting new technologies and techniques relevant to Niche

Qualification

Machine LearningPythonMLOpsSQLCloud PlatformsData ProcessingLeadershipCommunicationCollaborationMentoring

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