Staff Machine Learning Engineer

Summary

Join A Place for Mom as a Staff Machine Learning Engineer to build and deploy scalable machine learning models that solve business problems. You will own initiatives from concept to production, collaborating with cross-functional teams. The ideal candidate is self-motivated, goal-oriented, and experienced in identifying business value and communicating it effectively. Responsibilities include model development, maintenance, and monitoring, as well as mentoring other engineers. You will work closely with data scientists and engineers to ensure models align with business objectives. This role requires significant experience in machine learning and expertise in various technical skills.

Requirements

• Experience: 8+ years of experience in machine learning, with at least 2 years in a senior or staff-level ML engineering role, with a proven track record of delivering ML models to production with measurable impact
• Technical Skills : Expertise in SQL, Databricks, AWS services, Python, Spark and machine learning frameworks such as XGBoost, Scikit, TensorFlow, Keras or PyTorch. Experienced in developing, deploying, and serving scalable LLM applications in production environments
• Analytical Skills : Excellent analytical and problem-solving skills with a strong ability to derive insights from complex data sets
• Communication : Excellent communication skills with the ability to convey technical information and business impact to non-technical stakeholders
• Education : Master’s degree in Computer Science, Mathematics, or a related field, or equivalent working experience

Responsibilities

• Technical Leadership and Mentoring : Own and drive initiatives from idea to production, managing cross-functional stakeholders
• Drive architecture decisions and influence long-term strategy
• Provide ML-specific technical guidance and mentorship to the Engineering Org
• Machine Learning Model Development and Maintenance : Own the full ML lifecycle: from data exploration to model development, deployment, and continuous optimization
• Deep understanding of real-time inference systems, streaming data pipelines, model serving services, feature store monitoring and latency optimization for ML & LLM applications
• Solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks
• Run machine learning tests and experiments, and document findings and results
• Model Maintenance and Monitoring : Implement and monitor model and data quality checks to ensure accuracy and consistency of our models and pipelines in production
• Train, retrain, and monitor machine learning systems and models as needed
• Collaboration and Support : Collaborate with cross-functional teams, including date engineers, data scientists, machine learning engineers and product managers, to build machine learning applications that align with business objectives and best practices
• Provide support on model and data-related issues and queries from other teams including providing clear and actionable reporting for stakeholders
• Be comfortable working within the Engineering Organization while also using and influencing the ML Platforms and best practices established by the Data Organization
• Best Practices and Documentation Define and promote best practices for model implementation, training, evaluation, deployment, monitoring and continuous improvement

Benefits

• Base Salary: $150,000 to $170,000 + 20% Bonus
• 401(k) plus match
• Dental insurance
• Health insurance
• Vision Insurance
• Paid Time Off