Staff Machine Learning Engineer

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 :

Within 3 Months :

Within 6 Months :

Within 12 Months :

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-$190,400, 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

Team Interview - 45 Minutes

Leadership Interview - 30 Minutes

Why Niche ?

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.