Machine Learning Engineer (Remote)

📋 Description

• • Architect and implement end-to-end ML solutions that accelerate experimentation and model building across our entire product suite. You will own the full lifecycle—from data ingestion and feature engineering to model training, evaluation, and continuous deployment—ensuring that every experiment can be reproduced, scaled, and monitored in production.
• • Design and maintain robust microservices and RESTful APIs that serve state-of-the-art NLP and deep-learning models at low latency and high throughput. These services will power real-time recommendations, semantic search, and conversational AI features used by millions of students and mentors on the PeopleGrove platform.
• • Build and evolve scalable data pipelines using Python, Scala, and Apache Spark to transform raw, unstructured text into clean, enriched datasets ready for modeling. You will optimize for both batch and streaming workloads, leveraging tools such as Airflow, Kafka, and BigQuery to guarantee data quality, lineage, and governance.
• • Deploy and automate ML workflows on Google Cloud Platform (or equivalent), containerizing models with Docker, orchestrating them via Kubernetes, and monitoring them with Prometheus and Grafana. You will champion MLOps best practices—CI/CD for models, A/B testing frameworks, feature stores, and automated retraining—to reduce time-to-production from weeks to hours.
• • Collaborate daily with data scientists, product managers, and engineering squads to translate business goals into technical roadmaps. You will lead sprint planning, estimate effort, and balance cutting-edge research with pragmatic delivery, ensuring that every line of code directly impacts student success and mentor engagement.
• • Explore, prototype, and onboard emerging platforms, algorithms, and open-source libraries—such as transformers, diffusion models, or reinforcement learning—to keep PeopleGrove at the forefront of educational technology. You will document findings, run internal tech talks, and mentor junior engineers to foster a culture of continuous learning.
• • Establish and enforce coding standards, peer-review processes, and testing strategies that guarantee reliability, security, and compliance (FERPA, GDPR). As the team grows, you will shape hiring rubrics, onboarding playbooks, and architectural decision records that scale our R&D efforts globally.
• • Own the operational health of production ML systems, setting SLAs, alerting thresholds, and incident-response runbooks. You will conduct root-cause analyses, perform cost–performance optimizations, and present quarterly reviews to executive leadership, demonstrating how ML investments translate into measurable user outcomes.
• • Champion ethical AI practices by embedding fairness, transparency, and privacy safeguards into every model. You will partner with legal and compliance teams to conduct bias audits, generate explainability reports, and ensure that under-represented student populations benefit equitably from our technology.
• • Contribute to the open-source community by releasing internal tooling, publishing blog posts, and speaking at conferences. Your thought leadership will strengthen PeopleGrove’s employer brand and attract world-class talent to our mission of democratizing access to mentorship and career opportunities.