Machine Learning (ML) Engineer, Ranking & Retrieval, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home

Machine Learning (ML) Engineer, Ranking & Retrieval, Machine Learning (ML) and Artificial Intelligence (AI) Required, Work From Home

$120K/yr - $160K/yr

Human Resources

Information Technology

Recruiting

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

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Savings Plan Options
• PTO
• 100% remote work
• IT recruiting and staffing for financial services and trading.
• Naperville, Illinois, USA
• https://parallelpartners.com
• Leadership Team
• Saven Bellarmino
• President
• Company data provided by
• AI Tools
• Customize Your Resume
• Maximize your interview chances
• Build Cover Letter
• Make your application stand out
• Analyze How Well You Fit
• Understand your strength & weakness

Qualifications

• 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

Required skills

• Artificial Intelligence, Embeddings, JAX, Machine Learning, Model Evaluation, Modern Neural Architectures, Production Machine Learning Systems, PyTorch, Python, Ranking, Recommendation Systems, Retrieval, Vector Search

Experience

• Mid level