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Machine Learning Engineer, Ranking & Retrieval, Machine Learning, Artificial Intelligence
Parallel PartnersPosted 10/21/2026full-timeRemote • California • United States, MaliMid-LevelSenior💰 $120,000 - $160,000 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing Machine Learning models, with a strong focus on classification, ranking, and personalization. Proficient in developing and maintaining ML pipelines while ensuring model performance and reliability in production environments.
Highest-signal resume keywords
Machine Learning (ML) ExperienceArtificial Intelligence (AI) ExperienceProficiency in PythonExperience with PyTorch/JAXExperience in Classification and Personalization
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- 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
- Collaborate with engineering and product teams to deliver reliable ML-powered features
Requirements
What you’ll need- 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 and problem-solving skills
- Experience with embeddings, vector search and ranking models
- Experience with production Machine Learning (ML) systems and inference pipelines
- Proficiency in Python and PyTorch/JAX
- Willingness to complete a 60-minute coding assessment
Benefits
Comp & perks- Medical insurance
- Dental insurance
- Vision insurance
- Savings Plan Options
- PTO
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning (ML)Model EvaluationProduction-Quality CodeModel OptimizationClassificationRankingRetrievalRecommendation SystemsEmbeddingsVector Search
Soft Skills
Problem-Solving SkillsStrong Ownership
Tools & Technologies
PyTorchJAX
Industry Keywords
Neural ArchitecturesInference PipelinesModel Performance MetricsReal-World DatasetsHybrid Search