Staff Machine Learning Engineer

Summary

Join A Place for Mom as a Staff Machine Learning Engineer and build practical, data-driven machine learning applications. You will develop and deploy scalable ML models to solve business problems within core product areas, reporting to the VP of Engineering and collaborating with the Data Science team. The ideal candidate is self-motivated, goal-oriented, and capable of taking ownership of entire projects. You will own the full ML lifecycle, from data exploration to model deployment and optimization, and collaborate with cross-functional teams. You will also provide technical guidance and mentorship to the Engineering organization. This role requires expertise in various technologies and a proven track record of delivering impactful ML models to production. A Place for Mom offers competitive compensation and benefits.

Requirements

• 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
• 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
• Excellent analytical and problem-solving skills with a strong ability to derive insights from complex data sets
• Excellent communication skills with the ability to convey technical information and business impact to non-technical stakeholders
• Master’s degree in Computer Science, Mathematics, or a related field, or equivalent working experience

Responsibilities

• 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
• 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
• 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
• 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
• Define and promote best practices for model implementation, training, evaluation, deployment, monitoring and continuous improvement

Benefits

• 401(k) plus match
• Dental insurance
• Health insurance
• Vision Insurance
• Paid Time Off