Note: The job is a remote job and is open to candidates in USA. Parallel Partners is recruiting an Applied Machine Learning Engineer to build and improve machine-learning systems for AI-native applications. The role covers model development, evaluation, production deployment, and ongoing performance improvements across classification, retrieval, ranking, and personalization.
Responsibilities
- Build and improve Machine Learning (ML) models for classification, ranking, retrieval and personalization
- Develop efficient classifiers and optimize model accuracy, precision, latency and cost
- Improve search relevance and context retrieval using embeddings, hybrid search and reranking
- Build personalization models that learn from user behavior while respecting privacy
- Develop evaluation pipelines, labeled datasets and metrics to measure model quality
- Fine-tune and adapt existing models when supported by sufficient data
- Build and maintain Machine Learning (ML) training, inference and deployment pipelines
- Debug production issues, monitor model performance and ship improvements based on real-world feedback
Skills
- Machine Learning (ML) experience is required
- Artificial Intelligence (AI) experience is required
- Strong foundations in Machine Learning (ML) and modern neural architectures
- Hands-on experience building and deploying Machine Learning (ML) models in production
- Experience in classification, ranking, retrieval, recommendation systems or personalization
- Understanding of model evaluation, experimentation and performance metrics
- Comfortable writing production-quality code and working with real-world datasets
- Able to balance model quality, latency, cost and reliability
- Strong ownership, problem-solving skills
- Embeddings, vector search and ranking models, Production Machine Learning (ML) systems and inference pipelines, Python, and PyTorch/JAX
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Savings Plan Options
- PTO
- 100% Remote
Company Overview