Staff Machine Learning Engineer

Summary

Join A Place for Mom as a Staff Machine Learning Engineer to build and deploy scalable machine learning systems. Collaborate with data scientists and other teams to create AI-powered applications. You will be responsible for the entire ML lifecycle, from data exploration to model deployment and optimization. Leverage your expertise in statistics and programming to analyze large datasets and improve existing algorithms. Contribute to data pipeline development and maintenance, ensuring data quality and integrity. Collaborate with cross-functional teams and provide technical guidance and mentorship.

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
• Experience with statistical modeling
• Excellent communication skills with the ability to convey technical information and business impact to non-technical stakeholders
• Master’s degree in Computer Science, Statistics, 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 technical guidance and mentorship to a team of data scientists and machine leaning engineers
• 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
• Architect, build, and maintain robust and scalable data pipelines to support ML model training and inference
• Ensure data quality, integrity, and availability for all machine learning initiatives
• 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 data 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
• Define and promote best practices for model training, evaluation, deployment, monitoring and continuous improvement

Benefits

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